Archive for category Robotics

[Abstract] Neurotech: Robotic Assist Devices Show Gains in Walking for Crouch Gait in Cerebral Palsy and Post-Stroke Hemiparesis

via Neurotech: Robotic Assist Devices Show Gains in Walking for… : Neurology Today



Developers of robotic devices discuss advances in the technologies to help people improve walking post-stroke and improve couch gait in cerebral palsy. Independent experts in neurorehabilitation review the potential and possible caveats of these devices.

Three novel robotic assistance devices, one for hemiparetic gait following stroke, and two for crouch gait in children with cerebral palsy, have each demonstrated improved walking in preliminary clinical trials.

For stroke patients, a robotic exosuit made of a soft, clothing-like anchor attached to motorized cables was shown to increase the paretic limb’s forward propulsion and the paretic ankle’s swing phase dorsiflexion in both treadmill and over-ground walking.

For children with crouch gait due to cerebral palsy, one trial used a cable-driven robot called a Tethered Pelvic Assist Device, or TPAD. The laboratory-based device is designed to strengthen the extensor muscles, especially the soleus in the calves, by putting downward pressure on them during training. After six weeks of practice with the device, the children’s posture was more upright, with greater step length and toe clearance, when walking without it.

Also for children with crouch gait, the third study examined the use of a wearable exoskeleton that provides a burst of knee extension assistance at just the right moment when a child or adolescent is walking. None of the seven participants, age 5 to 17, fell while using it, and six of the seven showed postural improvements equivalent to those previously reported from surgery.

While promising, the devices will require far more testing in randomized trials before their true value can be known, said a leading specialist in neurological rehabilitation.

“These are foundational studies; they’re just beginning to get started,” said Bruce H. Dobkin, MD, FRCP, distinguished professor of clinical neurology and director of the Neurological Rehabilitation and Research Program at the Geffen School of Medicine at the University of California, Los Angeles. “The cost, safety, user-friendliness, and ability to use at differing levels of disability severity — all those are major challenges.”

Even so, each of the three devices employs a new kind of robotic assistance unlike any existing on the market.

“Most robotics for neurological injuries are heavy, power-hungry exosuits for people with spinal cord injuries who can’t walk at all,” said a coauthor of the study for stroke patients, Terry D. Ellis, PT, PhD, NCS, director of the Center for Neurorehabilitation at Boston University. “But there’s a whole bunch of people who have disabilities, who can walk, but don’t walk well. They need facilitation or augmentation to restore some of the normal components of walking.”


Published in the July 26 edition of Science Translational Medicine, the study of a robotic exosuit tested in nine post-stroke patients used what it called “garment-like, functional textile anchors” rather than a hard, metallic exterior. Worn on only the paretic limb, the suit was designed to be as unobtrusive as possible.

“It’s much more compatible with the real world than a rigid device would be,” said the first author of the paper, Louis N. Awad, PT, DPT, PhD, an assistant professor of physical therapy at Boston University, and a research faculty member at Spaulding Rehabilitation Hospital. “Ordinary clothes are made of soft material. We don’t don a metallic pair of pants and walk out the door. That’s our goal — robotic clothing that helps people with difficulty walking.”

Attached to cables tethered to a belt worn around the hips, the exosuit functioned in synchrony with a wearer’s paretic limb to facilitate an immediate increase in the paretic ankle’s swing phase dorsiflexion and forward propulsion (p< 0.05), according to the paper.

The improved movements resulted in a 20 percent reduction in forward propulsion interlimb asymmetry and a 10 percent reduction in the energy cost of walking, which together were equivalent to a nearly one-third lower metabolic burden — a 32 percent reduction — while walking.

Although the study did include some over-ground walking, it was not designed to test whether the exosuit had any therapeutic effects that might carry over to when patients are not wearing it.

“This is a proof of concept paper,” said Dr. Ellis. “Down the road we need to conduct trials in more ecologically valid environments, and to see if it has therapeutic value. For now we wanted to demonstrate that the device can facilitate more normal walking.”

While applauding the study as “clever,” Dr. Dobkin said it remained to be seen whether the robotic exosuit would prove to have significant therapeutic effects that would stand up in randomized trials in natural environments. He pointed to randomized trials published in recent years showing that peroneal nerve functional electrical stimulators have no greater therapeutic effect than do standard ankle-foot orthoses.

“It’s similar to all the work that was done using the electrical stimulation of the ankle,” Dr. Dobkin said. “The real question is whether it will lead to improved function when you walk over-ground. Walking on a treadmill is not terribly natural.”

He also pointed out that the nine patients in the study were able to walk on average at about two miles per hour. “That’s already pretty fast,” he said. In addition, he said, the 20 percent reduction in interlimb asymmetry is relatively modest.

But, said Dr. Dobkin, people can improve their gait by 20 percent just by sustained practice. “When you see modest changes like this with the device, you wonder if the same changes couldn’t have been achieved without it,” he said.

Steven L. Wolf, PhD, PT, FAPTA, FAHA, professor in the department of rehabilitation medicine at Emory University School of Medicine, pointed out that existing robotic devices to help people who are completely unable to walk can cost patients up to $250,000. Perhaps the exosuit might become an improvement over what presently exists both in terms of function and cost, he said.

“Most existing devices are beautiful but incredibly expensive,” Dr. Wolf said. “Is the bang in the buck? Not as yet, in my opinion. The evidence for persistent benefit from these device is just not there.”


The first of the two studies using robotic devices to improve crouch gait in children with cerebral palsy was published on July 26 in Science Robotics, led by senior author Sunil K. Agrawal, PhD, professor of mechanical engineering and rehabilitation medicine at Columbia University.

Rather than directly straighten the children’s posture, Dr. Agrawal’s seemingly contradictory approach was to increase the downward force on their pelvis as they attempted to walk on a treadmill. The tension in each wire, attached to a belt on the pelvis, is modulated in real time by a motor placed around the treadmill in response to motion capture data from cameras. Unlike other robotic devices that have been tested for treating crouch gait, the TPAD has no rigid links to the body, permitting free movement of the legs.

After training in the device for 15 sessions of 16 minutes each over the course of six weeks, the six participants showed enhanced upright posture, improved muscle coordination, increased step length, range of motion of the lower limb angles, toe clearance, and heel-to-toe pattern.

“You can see a marked difference before and after,” Dr. Agrawal said. “We heard from families and the children themselves that they were walking faster, with better posture. Now we have to see if we should use a higher magnitude of downward pull, how long each training session should be, and for how many sessions.”

Commenting on the TPAD study, Dr. Dobkin said, “The kids who were selected for inclusion were not necessarily the kind who get surgery. They had less of a crouch, a little bit more of a push-off. The question is whether training like this will lead to good over-ground walking. They got a hint of that.”

The second crouch-gait study, published on August 23 in Science Translational Medicine, involved a wearable exoskeleton designed for over-land use, and was described by the authors as the first robotic device designed specifically to treat a gait disorder in children and adolescents. Rather than force the lower limb to move in a particular way, “the exoskeleton dynamically changed the posture by introducing bursts of knee extension assistance during discrete portions of the walking cycle, a perturbation that resulted in maintained or increase knee extensor muscle activity during exoskeleton use,” the paper stated.

“In the last decade, there’s been a groundswell of work on exoskeletons, but a majority of them are designed to permit mobility after spinal injury in adults who have lost the ability to walk,” said senior author Thomas Bulea, PhD, a staff scientist in the functional and applied biomechanics section of the rehabilitation medicine department at the National Institutes of Health Clinical Center in Bethesda, MD. “There hasn’t been much done for the pediatric population who just need to improve their walking.”

A coauthor of the paper, Diane L. Damiano, PT, PhD, chief of the section in which Dr. Bulea works, said the purpose of the wearable exoskeleton is different than that of the TPAD device developed by Dr. Agrawal.

“His device is designed to strengthen the calf muscles by increasing the resistance on them,” she said. “His results were good, but this is very different from what we are doing. We have a wearable device. It’s not meant to be used in a lab for training. We’re not necessarily trying to strengthen them, although that would be a desired outcome; we are instead trying to assist their abilities to help them practice being more upright while they walk. This is something that they would wear throughout the day for several months with the goal that their posture will ultimately be improved without the device.”

A surprising observation, she added, was that some children saw it as something cool to wear.


•. Awad LN, Bae J, O’Donnell K, et al A soft robotic exosuit improves walking in patients after stroke Sci Transl Med 2017; 9 (400). pii: eaai9084.

•. Video of the soft robotic exosuit for stroke patients:

•. Kang J, Martelli D, Vashista V, et al Robot-driven downward pelvic pull to improve crouch gait in children with cerebral palsy Sci Robot 2017;2(8): eaan2634.

•. Video of the robot-driven downward pelvic pull device can be seen at

•. Lerner ZF, Damiano DL, Bulea TC. A lower-extremity exoskeleton improves knee extension in children with crouch gait from cerebral palsy Sci Transl Med 2017; 9 (404). pii: eaam9145.

, , , ,

Leave a comment

[Abstract+References] State-of-the-art robotic devices for ankle rehabilitation: Mechanism and control review

There is an increasing research interest in exploring use of robotic devices for the physical therapy of patients suffering from stroke and spinal cord injuries. Rehabilitation of patients suffering from ankle joint dysfunctions such as drop foot is vital and therefore has called for the development of newer robotic devices. Several robotic orthoses and parallel ankle robots have been developed during the last two decades to augment the conventional ankle physical therapy of patients. A comprehensive review of these robotic ankle rehabilitation devices is presented in this article. Recent developments in the mechanism design, actuation and control are discussed. The study encompasses robotic devices for treadmill and over-ground training as well as platform-based parallel ankle robots. Control strategies for these robotic devices are deliberated in detail with an emphasis on the assist-as-needed training strategies. Experimental evaluations of the mechanism designs and various control strategies of these robotic ankle rehabilitation devices are also presented.

1. De Ridder RWillems TVanrenterghem J, et al. Multi-segment foot landing kinematics in subjects with chronic ankle instability. Clin Biomech 2015; 30: 585592Google Scholar CrossrefMedline
2. Nolan KJYarossi MMcLaughlin PChanges in center of pressure displacement with the use of a foot drop stimulator in individuals with stroke. Clin Biomech 2015; 30: 755761Google Scholar CrossrefMedline
3. Kluding PMDunning KO’Dell MW, et al. Foot drop stimulation versus ankle foot orthosis after stroke: 30-week outcomes. Stroke 2013; 44: 16601669Google Scholar CrossrefMedline
4. Roy AForrester LWMacko RF, et al. Changes in passive ankle stiffness and its effects on gait function in people with chronic stroke. J Rehabil Res Dev 2013; 50: 555571Google Scholar CrossrefMedline
5. Roy AKrebs HIWilliams DJ, et al. Robot-aided neurorehabilitation: a novel robot for ankle rehabilitation. IEEE T Robot 2009; 25: 569582Google Scholar Crossref
6. Jamwal PKXie SQHussain S, et al. An adaptive wearable parallel robot for the treatment of ankle injuries. IEEE/ASME T Mech 2014; 19: 6475Google Scholar Crossref
7. Jamwal PKHussain SXie SQReview on design and control aspects of ankle rehabilitation robots. Disabil Rehabil Assist Technol 2015; 10: 93101Google Scholar CrossrefMedline
8. Gordon KESawicki GSFerris DPMechanical performance of artificial pneumatic muscles to power an ankle-foot orthosis. J Biomech 2006; 39: 18321841Google Scholar CrossrefMedline
9. Blaya JAHerr HAdaptive control of a variable-impedance ankle-foot orthosis to assist drop-foot gait. IEEE T Neur Sys Reh 2004; 12: 2431Google Scholar CrossrefMedline
10. Saglia JATsagarakis NGDai JS, et al. A high-performance redundantly actuated parallel mechanism for ankle rehabilitation. Int J Robot Res 2009; 28: 12161227Google Scholar Link
11. Jamwal PKHussain SXie SQThree-stage design analysis and multicriteria optimization of a parallel ankle rehabilitation robot using genetic algorithm. IEEE T Autom Sci Eng 2015; 12: 14331446Google Scholar Crossref
12. Jamwal PKXie SQAw KCKinematic design optimization of a parallel ankle rehabilitation robot using modified genetic algorithm. Robot Auton Syst 2009; 57: 10181027Google Scholar Crossref
13. Jamwal PKXie SQTsoi YH, et al. Forward kinematics modelling of a parallel ankle rehabilitation robot using modified fuzzy inference. Mech Mach Theory 2010; 45: 15371554Google Scholar Crossref
14. Burdea GCCioi DKale A, et al. Robotics and gaming to improve ankle strength, motor control, and function in children with cerebral palsy—a case study series. IEEE T Neur Sys Reh 2013; 21: 165173Google Scholar CrossrefMedline
15. Girone MBurdea GBouzit M, et al. A Stewart platform-based system for ankle telerehabilitation. Auton Robot 2001; 10: 203212Google Scholar Crossref
16. Bucca GBezzolato ABruni S, et al. A mechatronic device for the rehabilitation of ankle motor function. J Biomech Eng 2009; 131: 125001-1125001-7Google Scholar Crossref
17. Michmizos KPRossi SCastelli E, et al. Robot-aided neurorehabilitation: a pediatric robot for ankle rehabilitation. IEEE T Neur Sys Reh 2015; 23: 10561067Google Scholar CrossrefMedline
18. Xie SQJamwal PKAn iterative fuzzy controller for pneumatic muscle driven rehabilitation robot. Expert Syst Appl 2011; 38: 81288137Google Scholar Crossref
19. Jamwal PKHussain SGhayesh MH, et al. Impedance control of an intrinsically compliant parallel ankle rehabilitation robot. IEEE T Ind Electron 2016; 63: 36383647Google Scholar Crossref
20. Saglia JATsagarakis NGDai JS, et al. Control strategies for patient-assisted training using the ankle rehabilitation robot (ARBOT). IEEE/ASME T Mech 2013; 18: 17991808Google Scholar Crossref
21. Colombo GJoerg MSchreier R, et al. Treadmill training of paraplegic patients using a robotic orthosis. J Rehabil Res Dev 2000; 37: 693700Google Scholar Medline
22. Banala SKKim SHAgrawal SK, et al. Robot assisted gait training with active leg exoskeleton (ALEX). IEEE T Neur Sys Reh 2009; 17: 28Google Scholar CrossrefMedline
23. Melo PLSilva MTMartins JM, et al. Technical developments of functional electrical stimulation to correct drop foot: sensing, actuation and control strategies. Clin Biomech 2015; 30: 101113Google Scholar CrossrefMedline
24. Xu RJiang NMrachacz-Kersting N, et al. A closed-loop brain-computer interface triggering an active ankle-foot orthosis for inducing cortical neural plasticity. IEEE T Biomed Eng 2014; 61: 20922101Google Scholar CrossrefMedline
25. Jamwal PKHussain SMulticriteria design optimization of a parallel ankle rehabilitation robot: fuzzy dominated sorting evolutionary algorithm approach. IEEE T Syst Man Cy: S 2016; 46: 589597Google Scholar Crossref
26. Park YLChen BRPérez-Arancibia NO, et al. Design and control of a bio-inspired soft wearable robotic device for ankle-foot rehabilitation. Bioinspir Biomim 2014; 9: 117Google Scholar Crossref
27. Ferris DPGordon KESawicki GS, et al. An improved powered ankle-foot orthosis using proportional myoelectric control. Gait Posture 2006; 23: 425428Google Scholar CrossrefMedline
28. Veneman JFEkkelenkamp RKruidhof R, et al. A series elastic- and bowden-cable-based actuation system for use as torque actuator in exoskeleton-type robots. Int J Robot Res 2006; 25: 261281Google Scholar Link
29. Kinnaird CRFerris DPMedial gastrocnemius myoelectric control of a robotic ankle exoskeleton. IEEE T Neur Sys Reh 2009; 17: 3137Google Scholar CrossrefMedline
30. Bharadwaj KSugar TGKoeneman JB, et al. Design of a robotic gait trainer using spring over muscle actuators for ankle stroke rehabilitation. J Biomech Eng 2005; 127: 10091013Google Scholar CrossrefMedline
31. Hollander KWIlg RSugar TG, et al. An efficient robotic tendon for gait assistance. J Biomech Eng 2006; 128: 788791Google Scholar CrossrefMedline
32. Ward JSugar TBoehler A, et al. Stroke survivors’ gait adaptations to a powered ankle foot orthosis. Adv Robot 2011; 25: 18791901Google Scholar CrossrefMedline
33. Shorter KAKogler GFLoth E, et al. A portable powered ankle-foot orthosis for rehabilitation. J Rehabil Res Dev 2011; 48: 459472Google Scholar CrossrefMedline
34. Malcolm PDerave WGalle S, et al. A simple exoskeleton that assists plantarflexion can reduce the metabolic cost of human walking. PLoS ONE 2013; 8: 17Google Scholar Crossref
35. Galle SMalcolm PDerave W, et al. Enhancing performance during inclined loaded walking with a powered ankle–foot exoskeleton. Eur J Appl Physiol 2014; 114: 23412351Google Scholar CrossrefMedline
36. Erdogan ACelebi BSatici AC, et al. AssistOn-Ankle: a reconfigurable ankle exoskeleton with series-elastic actuation. Auton Robot 2016; 41: 116Google Scholar
37. Noël MCantin BLambert S, et al. An electrohydraulic actuated ankle foot orthosis to generate force fields and to test proprioceptive reflexes during human walking. IEEE T Neur Sys Reh 2008; 16: 390399Google Scholar CrossrefMedline
38. Borràs JThomas FTorras CNew geometric approaches to the analysis and design of Stewart–Gough platforms. IEEE/ASME T Mech 2014; 19: 445455Google Scholar Crossref
39. Yoon JRyu JLim KBReconfigurable ankle rehabilitation robot for various exercises. J Robotic Syst 2006; 22: S15S33Google Scholar Crossref
40. Karime AAl-Osman HAlja’Am JM, et al. Tele-wobble: a telerehabilitation wobble board for lower extremity therapy. IEEE T Instrum Meas 2012; 61: 18161824Google Scholar Crossref
41. Dai JSZhao TNester CSprained ankle physiotherapy based mechanism synthesis and stiffness analysis of a robotic rehabilitation device. Auton Robot 2004; 16: 207218Google Scholar Crossref
42. Wang CFang YGuo S, et al. Design and kinematical performance analysis of a 3-RUS/RRR redundantly actuated parallel mechanism for ankle rehabilitation. J Mech Robot 2013; 5: 041003-1041003-7Google Scholar Crossref
43. Rakhodaei HSaadat MRastegarpanah A, et al. Path planning of the hybrid parallel robot for ankle rehabilitation. Robotica 2016; 34: 173184Google Scholar Crossref
44. Vallés MCazalilla JValera Á, et al. A 3-PRS parallel manipulator for ankle rehabilitation: towards a low-cost robotic rehabilitation. Robotica 2017; 35: 19391957Google Scholar Crossref
45. Tsoi YHXie SQDesign and control of a parallel robot for ankle rehabilitation. Int J Intell Syst Tech Appl 2010; 8: 100113Google Scholar
46. Lin CCKJu MSChen SM, et al. A specialized robot for ankle rehabilitation and evaluation. J Med Biol Eng 2008; 28: 7986Google Scholar
47. Agrawal ASangwan VBanala SK, et al. Design of a novel two degree-of-freedom ankle-foot orthosis. J Mech Des: T ASME 2007; 129: 11371143Google Scholar Crossref
48. Wolbrecht ETReinkensmeyer DJBobrow JEPneumatic control of robots for rehabilitation. Int J Robot Res 2010; 29: 2338Google Scholar Link
49. Gordon KEFerris DPLearning to walk with a robotic ankle exoskeleton. J Biomech 2007; 40: 26362644Google Scholar CrossrefMedline
50. Forrester LWRoy AKrebs HI, et al. Ankle training with a robotic device improves hemiparetic gait after a stroke. Neurorehabil Neural Repair 2011; 25: 369377Google Scholar Link
51. Forrester LWRoy AGoodman RN, et al. Clinical application of a modular ankle robot for stroke rehabilitation. NeuroRehabilitation 2013; 33: 8597Google Scholar Medline
52. Koller JRJacobs DAFerris DP, et al. Learning to walk with an adaptive gain proportional myoelectric controller for a robotic ankle exoskeleton. J Neuroeng Rehabil 2015; 12: 114Google Scholar CrossrefMedline
53. Gordon KEKinnaird CRFerris DPLocomotor adaptation to a soleus EMG-controlled antagonistic exoskeleton. J Neurophysiol 2013; 109: 18041814Google Scholar CrossrefMedline
54. Shorter KAXia JHsiao-Wecksler ET, et al. Technologies for powered ankle-foot orthotic systems: possibilities and challenges. IEEE/ASME T Mech 2013; 18: 337347Google Scholar Crossref
55. Zanotto DAkiyama YStegall P, et al. Knee joint misalignment in exoskeletons for the lower extremities: effects on user’s gait. IEEE T Robot 2015; 31: 978987Google Scholar Crossref
56. Cempini MDe Rossi SMMLenzi T, et al. Self-alignment mechanisms for assistive wearable robots: a kinetostatic compatibility method. IEEE T Robot 2013; 29: 236250Google Scholar Crossref
57. Stienen AHAHekman EEGvan der Helm FCT, et al. Self-aligning exoskeleton axes through decoupling of joint rotations and translations. IEEE T Robot 2009; 25: 628633Google Scholar Crossref
58. Tsoi YHXie SQOnline estimation algorithm for a biaxial ankle kinematic model with configuration dependent joint axes. J Biomech Eng 2011; 133: 021005-1021005-11Google Scholar Crossref

Source: State-of-the-art robotic devices for ankle rehabilitation: Mechanism and control reviewProceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine – Shahid Hussain, Prashant K Jamwal, Mergen H Ghayesh, 2017

, ,

Leave a comment

[ARTICLE] Is two better than one? Muscle vibration plus robotic rehabilitation to improve upper limb spasticity and function: A pilot randomized controlled trial – Full Text


Even though robotic rehabilitation is very useful to improve motor function, there is no conclusive evidence on its role in reducing post-stroke spasticity. Focal muscle vibration (MV) is instead very useful to reduce segmental spasticity, with a consequent positive effect on motor function. Therefore, it could be possible to strengthen the effects of robotic rehabilitation by coupling MV. To this end, we designed a pilot randomized controlled trial (Clinical Trial NCT03110718) that included twenty patients suffering from unilateral post-stroke upper limb spasticity. Patients underwent 40 daily sessions of Armeo-Power training (1 hour/session, 5 sessions/week, for 8 weeks) with or without spastic antagonist MV. They were randomized into two groups of 10 individuals, which received (group-A) or not (group-B) MV. The intensity of MV, represented by the peak acceleration (a-peak), was calculated by the formula (2πf)2A, where f is the frequency of MV and A is the amplitude. Modified Ashworth Scale (MAS), short intracortical inhibition (SICI), and Hmax/Mmax ratio (HMR) were the primary outcomes measured before and after (immediately and 4 weeks later) the end of the treatment. In all patients of group-A, we observed a greater reduction of MAS (p = 0.007, d = 0.6) and HMR (p<0.001, d = 0.7), and a more evident increase of SICI (p<0.001, d = 0.7) up to 4 weeks after the end of the treatment, as compared to group-B. Likewise, group-A showed a greater function outcome of upper limb (Functional Independence Measure p = 0.1, d = 0.7; Fugl-Meyer Assessment of the Upper Extremity p = 0.007, d = 0.4) up to 4 weeks after the end of the treatment. A significant correlation was found between the degree of MAS reduction and SICI increase in the agonist spastic muscles (p = 0.004). Our data show that this combined rehabilitative approach could be a promising option in improving upper limb spasticity and motor function. We could hypothesize that the greater rehabilitative outcome improvement may depend on a reshape of corticospinal plasticity induced by a sort of associative plasticity between Armeo-Power and MV.


Spasticity is defined as a velocity-dependent increase in muscle tone due to the hyper-excitability of muscle stretch reflex [1]. Spasticity of the upper limb is a common condition following stroke and traumatic brain injury and needs to be assessed carefully because of the significant adverse effects on patient’s motor functions, autonomy, and quality of life [2].

Different pharmacological and non-pharmacological approaches are currently available for upper limb spasticity management, as physiotherapy (including magnetic stimulation, electromagnetic therapy, sensory-motor techniques, and functional electrical stimulation treatment) and robot-assisted therapy [34]. In this regard, several studies suggest robotic devices, including the Armeo® (a robotic exoskeleton for the rehabilitation of upper limbs), may help reducing spasticity by modifying spasticity-related synaptic processes at either the brain or spinal level [513], resulting in spasticity reduction in antagonist muscles through, e.g., a strengthening of spinal reciprocal inhibition mechanisms [11].

Growing research is proposing segmental muscle vibration (MV) as being a powerful tool for the treatment of focal spasticity in post-stroke patients [1415]. Mechanical devices deliver low-amplitude/high-frequency vibratory stimuli to specific muscles [1617], thus offering strong proprioceptive inputs by activating the neural pathway from muscle spindle annulospiral endings to Ia-fiber, dorsal column–medial lemniscal pathway, the ventral posterolateral nucleus of the thalamus (and other nuclei of the basal ganglia), up to the primary somatosensory area (postcentral gyrus and posterior paracentral lobule of the parietal lobe), and the primary motor cortex [1819]. At the cortical network level, proprioceptive inputs can alter the excitability of the corticospinal pathway by modulating intracortical inhibitory and facilitatory networks within primary sensory and motor cortex, and affecting the strength of sensory inputs to motor circuits [2022]. In particular, periods of focal MV delivered alone can modify sensorimotor organization within the primary motor cortex (i.e., can increase or decrease motor evoked potential—MEP—and short intracortical inhibition (SICI) magnitude in the vibrated muscles, while opposite changes occur in the neighboring muscles), thus reducing segmental hyper-excitability and spasticity [2022].

While focal MV is commonly used to reduce upper limb post-stroke spasticity, there is no conclusive evidence on the role of robotic rehabilitation in such a condition [1417,2327]. A strengthening of the effects of neurorobotics and MV on spasticity could be achieved by combining MV and neurorobotics. The rationale for combining Armeo-Power and MV to reduce spasticity could lie in the summation and amplification of their single modulatory effects on corticospinal excitability [28]. Specifically, it is hypothesizable that MV may strengthen the learning-dependent plasticity processes within sensory-motor areas that are in turn triggered by the intensive, repetitive, and task-oriented movement training offered by Armeo-Power [2930]. Such an amplification may depend on a sort of associative plasticity (i.e., the one generated by timely coupling two different synaptic inputs) between MV and Armeo-Power [3133].

To the best of our knowledge, this is the first attempt to investigate such approach. Indeed, a previous study combining MV with conventional physiotherapy used Armeo only as evaluating tool [14].

The aim of our study was to assess whether a combined protocol employing MV and Armeo-Power training, as compared to Armeo-Power alone, may improve upper limb spasticity and motor function in patients suffering from a hemispheric stroke in the chronic phase. To this end, we compared the clinical and electrophysiological after-effects of Armeo-Power with or without MV on upper limb spasticity. We also assessed the effects on upper limb motor function and muscle activation, disability burden, and mood, given that spasticity may have significant negative consequences on these outcomes. Further, it is important to evaluate mood, as it may negatively affect functional recovery [3436], increase mortality [37], and weaken the compliance of the patient to the rehabilitative training [3839].[…]

Continue —>  Is two better than one? Muscle vibration plus robotic rehabilitation to improve upper limb spasticity and function: A pilot randomized controlled trial


Fig 2. Combined rehabilitative approach.

, , , , , ,

Leave a comment

[Abstract] Recent Advances on Lower Limb Exoskeleton Rehabilitation Robot


Background: Lower limb exoskeleton rehabilitation robot is a bionic robot, which is the product of the combination of medical technology and robot technology, simulating human walking movement. It can be mainly used for rehabilitation training of patients with lower limb dysfunction.

Objective: To provide an overview of recent lower limb exoskeleton rehabilitation robot and introduce their respective characteristics and development.

Method: A recent lower limb exoskeleton rehabilitation robot is divided into passive drive, pneumatic drive, hydraulic drive and motor drive. This paper reviews various representative patents related to lower limb exoskeleton rehabilitation robot. The structural characteristics and applications of the typical lower limb exoskeleton rehabilitation robots are introduced.

Results: The differences between different types of lower limb exoskeleton rehabilitation robots are compared and analyzed, and the structural characteristics are concluded. The main problems in its development are analyzed, the development trend is foreseen, and the current and future research of the patents on lower limb exoskeleton rehabilitation robot is discussed.

Conclusion: There are a lot of patents and articles about the exoskeleton rehabilitation robots, however, if these problems can be solved, such as small size, light weight and high power output are solved at the same time, the consistency with human body will be advanced, with the combination of traditional rehabilitation medicine. It will be possible to maximize the rehabilitation of the lower limbs.

Source: Recent Advances on Lower Limb Exoskeleton Rehabilitation Robot: Ingenta Connect

, , , , , , ,

Leave a comment

[ARTICLE] Design and Interaction Control of a New Bilateral Upper-Limb Rehabilitation Device – Full Text


This paper proposed a bilateral upper-limb rehabilitation device (BULReD) with two degrees of freedom (DOFs). The BULReD is portable for both hospital and home environment, easy to use for therapists and patients, and safer with respect to upper-limb robotic exoskeletons. It was implemented to be able to conduct both passive and interactive training, based on system kinematics and dynamics, as well as the identification of real-time movement intention of human users. Preliminary results demonstrate the potential of the BULReD for clinical applications, with satisfactory position and interaction force tracking performance. Future work will focus on the clinical evaluation of the BULReD on a large sample of poststroke patients.

1. Introduction

In the United States, more than 700,000 people suffer from stroke each year, and approximately two-thirds of these individuals survive and require rehabilitation [1]. In New Zealand (NZ), there are an estimated 60,000 stroke survivors, and many of them have mobility impairments [2]. Stroke is the third reason for health loss and takes the proportion of 3.9 percent, especially for the group starting on middle age, suffering the stroke as a nonfatal disease in NZ [3]. Professor Caplan who studies Neurology at Harvard Medical School describes stroke as a term which is a kind of brain impairment as a result of abnormal blood supply in a portion of the brain [4]. The brain injury is most likely leading to dysfunctions and disabilities. These survivors normally have difficulties in activities of daily living, such as walking, speaking, and understanding, and paralysis or numbness of the human limbs. The goals of rehabilitation are to help survivors become as independent as possible and to attain the best possible quality of life.

Physical therapy is conventionally delivered by the therapist. While this has been demonstrated as an effective way for motor rehabilitation [5], it is time-consuming and costly. Treatments manually provided by therapists require to take place in a specific environment (in a hospital or rehabilitation center) and may last several months for enhanced rehabilitation efficacy [6]. A study by Kleim et al. [7] has shown that physical therapy like regular exercises can improve plasticity of a nervous system and then benefits motor enrichment procedures in promoting rehabilitation of brain functional models. It is a truth that physical therapy should be a preferable way to take patients into regular exercises and guided by a physical therapist, but Chang et al. [8] showed that it is a money-consuming scheme. Robot-assisted rehabilitation solutions, as therapeutic adjuncts to facilitate clinical practice, have been actively researched in the past few decades and provide an overdue transformation of the rehabilitation center from labor-intensive operations to technology-assisted operations [9]. The robot could also provide a rich stream of data from built-in sensors to facilitate patient diagnosis, customization of the therapy, and maintenance of patient records. As a popular neurorehabilitation technique, Liao et al. [10] indicated that robot-assisted therapy presents market potential due to quantification and individuation in the therapy session. The quantification of robot-assisted therapy refers that a robot can provide consistent training pattern without fatigue with the given parameter. The characterization of individuation allows therapists to customize a specific training scheme for an individual.

Many robotic devices have been developed in recent years for stroke rehabilitation and show great potential for clinical applications [1112]. Typical upper-limb rehabilitation devices are MIME, MIT-Manus, ARM Guide, NeReBot, and ARMin [51321]. Relevant evidences demonstrated that these robots are effective for upper-limb rehabilitation but mostly for the one side of the human body. Further, upper-limb rehabilitation devices can be unilateral or bilateral [2224]. Despite the argument between these two design strategies, bilateral activities are more common than unilateral activities in daily living. Liu et al. [25] pointed that the central nervous system dominates the human movement with coordinating bilateral limb to act in one unit instead of independent unilateral actions. From this point, bilateral robots are expected to be more potential than unilateral devices. Robotic devices for upper-limb rehabilitation can be also divided into two categories in terms of structure: the exoskeleton and the end-effector device [26]. Two examples of upper-limb exoskeletons are the arm exoskeleton [27] and the RUPERT IV [28]. In addition, Lum et al. [13] incorporated a PUMA 560 robot (Staubli Unimation Inc., Duncan, South Carolina) to apply forces to the paretic limbs in the MIME system. This robotic device can be made for both unilateral and bilateral movements in a three-dimensional space. To summarize, existing robotic exoskeletons for upper-limb rehabilitation are mostly for unilateral training.

There are some devices that have been specially designed for bilateral upper-limb training for poststroke rehabilitation. van Delden et al. [29] conducted a systematic review to provide an overview and qualitative evaluation of the clinical applications of bilateral upper-limb training devices. A systematic search found a total of six mechanical devices and 14 robotic bilateral upper-limb training devices, with a comparative analysis in terms of mechanical and electromechanical characteristics, movement patterns, targeted part, and active involvement of the upper limb, training protocols, outcomes of clinical trials, and commercial availability. Obviously, these mechanical devices require the human limbs to actively move for training, while the robotic ones can be operated in both passive and active modes. However, few of these robotic bilateral upper-limb training devices have been commercially available with current technology. For example, the exoskeleton presented in [30] requires the development of higher power-to-weight motors and structural materials to make it mobile and more compact.

The University of Auckland developed an end-effector ReachHab device to assist bilateral upper-limb functional recovery [31]. However, this device suffered from some limitations, such as deformation of the frame leading to significant vibration, also hard to achieve satisfactory control performance. This paper presents the design and interaction control of an improved bilateral upper-limb rehabilitation device (BULReD). This device is portable for both hospital and home environment, easy to use for therapists and patients, and safer with respect to upper-limb robotic exoskeletons. This paper is organized as follows. Following Introduction, a detailed description of the BULReD is given, including mechanical design, electrical design, kinematics, and dynamics. Then, the control design is presented for both passive training and interactive training, as well as the fuzzy-based adaptive training. Experiments and Results is introduced next and the last is Conclusion.[…]

Continue —>  Design and Interaction Control of a New Bilateral Upper-Limb Rehabilitation Device

, , , , , , ,

Leave a comment

[ARTICLE] Adaptive hybrid robotic system for rehabilitation of reaching movement after a brain injury: a usability study – Full Text



Brain injury survivors often present upper-limb motor impairment affecting the execution of functional activities such as reaching. A currently active research line seeking to maximize upper-limb motor recovery after a brain injury, deals with the combined use of functional electrical stimulation (FES) and mechanical supporting devices, in what has been previously termed hybrid robotic systems. This study evaluates from the technical and clinical perspectives the usability of an integrated hybrid robotic system for the rehabilitation of upper-limb reaching movements after a brain lesion affecting the motor function.


The presented system is comprised of four main components. The hybrid assistance is given by a passive exoskeleton to support the arm weight against gravity and a functional electrical stimulation device to assist the execution of the reaching task. The feedback error learning (FEL) controller was implemented to adjust the intensity of the electrical stimuli delivered on target muscles according to the performance of the users. This control strategy is based on a proportional-integral-derivative feedback controller and an artificial neural network as the feedforward controller. Two experiments were carried out in this evaluation. First, the technical viability and the performance of the implemented FEL controller was evaluated in healthy subjects (N = 12). Second, a small cohort of patients with a brain injury (N = 4) participated in two experimental session to evaluate the system performance. Also, the overall satisfaction and emotional response of the users after they used the system was assessed.


In the experiment with healthy subjects, a significant reduction of the tracking error was found during the execution of reaching movements. In the experiment with patients, a decreasing trend of the error trajectory was found together with an increasing trend in the task performance as the movement was repeated. Brain injury patients expressed a great acceptance in using the system as a rehabilitation tool.


The study demonstrates the technical feasibility of using the hybrid robotic system for reaching rehabilitation. Patients’ reports on the received intervention reveal a great satisfaction and acceptance of the hybrid robotic system.


Upper limb hemiparesis is one of the most common consequences after a brain injury accident [1]. This motor impairment has an adverse impact on the quality of life of survivors since it hinders the execution of activities of daily living. From the rehabilitation perspective, it is widely accepted that high-intensity and repetitive task-specific practice is the most effective principle to promote motor recovery after a brain injury [12]. However, traditional rehabilitation treatment offers a dose of movement repetition that is in most cases insufficient to facilitate neural reorganization [3]. In response to these current clinical shortcomings, there is a clear interest in alternative rehabilitation methods that improve the arm motor functionality of brain injury survivors.

Hybrid robotic systems for motor rehabilitation are a promising approach that combine the advantages of robotic support or assistive devices and functional electrical stimulation (FES) technologies to overcome their individual limitations and to offer more robust rehabilitation interventions [4]. Despite the potential benefits of using hybrid robotic systems for arm rehabilitation, a recent published review shows that only a few hybrid systems presented in the literature were tested with stroke patients [4]. Possible reasons could be the difficulties arising from the integration of both assistive technologies or the lack of integrated platforms that can be easily setup and used.

End-effector robotic devices combined with FES represent the most typical hybrid systems used to train reaching tasks under constrained conditions [567]. With these systems, patients’ forearms are typically restricted to the horizontal plane to isolate the training of the elbow extension movement. The main advantage of this approach is the simplicity of the setup, with only 1 Degree of Freedom (DoF). However, to maximize the treatment’s outcomes and achieve functional improvement it is necessary to train actions with higher range of motion (> 1 DoF) and functional connotations [89]. Yet, the complexity for driving a successful movement execution in such scenarios requires the implementation of a robust and reliable FES controller.

The appropriate design and implementation of FES controllers play a key role to achieve stable and robust motion control in hybrid robotic systems. The control strategy must be able to drive all the necessary joints to realize the desired movement, and compensate any disturbances to the motion, i.e. muscle fatigue onset as well as the strong nonlinear and time-varying response of the musculoskeletal system to FES [1011]. Consequently, open-loop and simple feedback controllers (e.g. proportional-integral-derivative -PID-) are not robust enough to cope with these disturbances [812]. Meadmore et al. presented a more suitable hybrid robotic system for functional rehabilitation scenarios [13]. They implemented a model-based iterative learning controller (ILC) that adjusts the FES intensity based on the tracking error of the previously executed movement (see [1314] for a detail description of the system). This iterative adjustment allows compensating for disturbances caused by FES. Although this approach addresses some of the issues regarding motion control with FES, it requires a detailed mathematical description of the musculoskeletal system to work properly. In this context, unmodeled dynamics and the linearization of the model can reduce the robustness of the controller performance. Also, the identification of the model’s parameters is complex and time consuming, which limits its applicability in clinical settings [1112].

The Feedback Error Learning (FEL) scheme proposed by Kawato [15] can be considered as an alternative to ILC. This scheme was developed to describe how the central nervous system acquires an internal model of the body to improve the motor control. Under this scheme, the motor control command of a feedback controller is used to train a feedforward controller to learn implicitly the inverse dynamics of the controlled system on-line (i.e. the arm). Complementary, this on-line learning procedure also allows the controller to adapt and compensate for disturbances. In contrast with the ILC, the main advantage of this strategy is that the controller does not require an explicit model of the controlled system to work correctly and that it can directly learn the non-linear characteristic of the controlled system. Therefore, using the FEL control strategy to control a hybrid robotic system can simplify the setup of the system considerably, which makes easier to deploy it in clinical settings as well as personalize its response according to each patient’s musculoskeletal characteristics and movement capabilities. The FEL has been used previously to control the wrist [16] and the lower limb [17] motion with FES in healthy subjects; but it has not been tested on brain injury patients. In a previous pilot study, we partially showed the suitability of the FEL scheme in hybrid robotic systems for reaching rehabilitation with healthy subjects [18]. However, a rigorous and robust analysis has not been presented neither this concept has not been tested with motor impaired patients.

The main objective of this study is to verify the usability of a fully integrated hybrid robotic system based on an FEL scheme for rehabilitation of reaching movement in brain injury patients. To attain such objective two-step experimentation was followed. The first part consists of demonstrating the technical viability and learning capability of the developed FEL controller to drive the execution of a coordinated shoulder-elbow joint movement. The second part consists of testing the usability of the platform with brain injury patients in a more realistic rehabilitation scenario. For this purpose, we assessed the patients’ performance and overall satisfaction and emotional response after using the system.


In this section, we present the hybrid robotic system for the rehabilitation of reaching movement in patients with a brain injury. The system focuses on aiding users to move their paretic arm towards specific distal directions in the space. During the execution of the reaching task, the FEL controller adjusts the intensities of the electrical stimuli delivered to target muscles in order to aid the subjects in tracking accurately the target paths.

Description of the hybrid rehabilitation platform for reaching rehabilitation

Figure 1 shows the general overview of the developed platform. This rehabilitation platform is composed of four main components: the hybrid assistive device (upper limb exoskeleton + FES device); the high-level controller (HLC); the visual feedback and; the user interface. […]

Fig. 1 a General overview of the presented hybrid robotic platform for reaching rehabilitation. bVisual feedback provided to the users. The green ball represents the actual arm position, the blue cross is the reference trajectory, the initial and final position are represented by the gray ball and red square respectively. c Interface for system configuration

Source: Adaptive hybrid robotic system for rehabilitation of reaching movement after a brain injury: a usability study | Journal of NeuroEngineering and Rehabilitation | Full Text

, , , ,

Leave a comment

[ARTICLE] A wearable somatosensory teaching device with adjustable operating force for gait rehabilitation training robot – Full Text

A novel wearable multi-joint teaching device for lower-limb gait rehabilitation is presented, intended to facilitate the adjustment of training modes in unique requirements of patients. A physiotherapist manipulates this active teaching device to plan the personalized gait trajectory and to construct the individual training mode. A haptic interaction joint module that stems from the friction braking principle is outlined here, with an adjustable operating force exerted by pneumatic film cylinders. With dual functions of somatosensory perception and teaching, it provides physiotherapist with a smooth and comfortable operation and a kind of force telepresence. The main contents are elaborated including the structural design and pneumatic proportional servo system of the teaching device and the joint module, operating force control principle, and gravity compensation method. Through performance tests of the prototype, the adjustable operating force has been demonstrated with the characteristics of good linearity and response speed. The results of master–slave control experiments preliminarily verified the effectiveness of the control approach. The research on the novel somatosensory teaching device with master–slave teaching mode has provided a concise, convenient, and efficient means for the clinical application of lower-limb rehabilitation robots, presumably as a new idea and technical supports for the future design.

Based on the neuroplasticity principle,1 a lower-limb rehabilitation training robot is a kind of automatic equipment that can recover or rebuild neural pathways2,3 for patients with motor dysfunction. The clinical presentation of a spinal cord injury (SCI) or a stroke comprises motor weakness or complete paresis, complete or partial loss of sensory function. The Swedish therapist Brunnstrom proposed the famous six-recovery-stage theory. Based on this theory, the training has different aims in the early stage of rehabilitation (flaccid paralysis stage), middle stage of rehabilitation (spasm stage), and later stage of rehabilitation (recovery stage). One major principle of neurological rehabilitation is that of motor learning. According to the principle of neural plasticity, repetitive and specific training tasks, which make the cerebral cortex learn and store the correct movement patterns, are important and effective. During rehabilitation, patients have to relearn motor tasks in order to overcome disability and limitations in the completion of daily activities. This is the theoretical basis of rehabilitation treatment. For a robot, the control strategy is provided diversely in different stages of rehabilitation to eliminate abnormal movement patterns. In the early rehabilitation, the passive training mode is usually adopted to help patients according to the predetermined trajectory and improve exercise capacity and reduce muscle atrophy. Then the active assist training mode begins for the patients of the middle recovery stage with moderate strength and relieving muscle spasm. In the later rehabilitation stage, the active resist training mode can be used to encourage patients to participate initiatively. The effect and importance of rehabilitation robots have been internationally recognized.48

Giving different state of an illness exhibited by hemiparetic individuals and the different training modes as mentioned above, the gait rehabilitation training robot primarily entails customized designing the parameters including movement trajectory, training speed and strength, and real-time perceiving, adjusting, and controlling. Lower-limb exoskeleton mechanism features of many degrees of freedom, together with the individual and condition differences of patients, so the problems are highlighted about how to accurately plan the correct gait trajectory and how to adjust training modes on time according to the progression. These issues become one of the research foci and technical difficulties of rehabilitation robot.

Most of the typical lower-limb rehabilitation robots in the world are autonomously controlled. The gait training mode planning for them is summarized in two methods, that is, preselected by a physiotherapist and dynamically adjusted by the algorithm. For some representative examples, the horizontal rehabilitation training robot Motion Maker9 can automatically guide patients along a preselected trajectory to perform passive flexion movement training on hip, knee, and ankle joints. The Lokomat1012 is a kind of body-weight-supported treadmill training (BWSTT) robot that adjusts the assisted power or reference trajectory by the impedance algorithm according to the patient interaction force. Patients can be made available to active and passive training mode. In the case of the lower extremity powered exoskeleton (LOPES) gait rehabilitation robot,13,14 limb reference trajectory is generated by instantaneous mapping with the healthy limb movement. The feasibility and functional improvements achieved in response to the emergence of such self-control rehabilitation robot; however, the existing technological bottleneck is obvious, that is, the limited adaptability of training mode.

The objective of this research is to develop a gait trajectory teaching device, with which the physiotherapist can directly and professionally teach to the robot and therefore present complex actions and adjust training modes as needed. Through master–slave teaching method, such system may provide the adaptability of the robot-mediated training and improve the treatment quality and efficiency, and decrease the difficulties in control algorithm study and the contradiction between the complex algorithms and real-time control.

Because of the more elaborate actions of the upper extremity and hand, teaching and playback technology is first applied to upper-limb rehabilitation training robot, for example, the flexible force feedback master–slave exoskeleton manipulator developed by America General Electric Company,15 the wearable master–slave training equipment of upper limbs driven by pneumatic artificial muscles in Okayama University in Japan,16 and the remotely operated upper-limb training robot of Southeast University in China.17 But there are fewer applications for lower-limb rehabilitation training. A single-joint ankle-foot orthoses designed by Canada, the Centre for Interdisciplinary Research in Rehabilitation and Social Integration is introduced in the literature.18The main cylinder driven by a motor controlled the slave cylinder to drive the orthoses. As described in a literature,19 a wearable master–slave lower-limb training robot driven by pneumatic artificial muscle achieves the teaching and training for the knee and ankle rehabilitation by sensors feeding back the trainer joint torque to the main control mechanism. In most of the studies mentioned above, the limitations existing in master–slave teaching for the lower-limb rehabilitation training robot can be summarized as follows: (1) the teaching device has the characteristics of complex structure, large quality and high inertia, so the physiotherapist is laborious and feels fatigue quickly, (2) the coordinate of the multi joints is demanded highly which may lead to the insufficient operating smoothness of the device, and (3) the feedback joint torque cannot be directly perceived by the physiotherapist but only as the control signal for the device.

In light of the above limitations, a novel multi-joint wearable teaching device is developed with adjustable operating force, which is exerted by light film cylinders. Based on the gravity compensation control method, a physiotherapist operates the teaching device to plan training trajectory smoothly and comfortably while also perceive the scene interaction force came from patients. In this manner, our research solved the existing problems, namely, the weight, the difficult manipulation of the teaching and the less force feedback to the physiotherapist. He operates the teaching device with the master–slave mode may provide various training modes fast and intuitively. The force telepresence from patients makes physiotherapist better controlling the training intensity and realizing the individual rehabilitation training consultation.

In this article, we elaborate five major contents that have been derived from this research as follows: master–slave teaching system solution, structural design of the multi-joint wearable master teaching device, operating force regulation principle and gravity compensation method, operating force regulation performance experiments, and master–slave control experiments.

Figure 1. System overall scheme.

Continue —> A wearable somatosensory teaching device with adjustable operating force for gait rehabilitation training robotAdvances in Mechanical Engineering – Bingjing Guo, Jianhai Han, Xiangpan Li, Peng Wu, Yanbin Zhang, Aimin You, 2017

, , , ,

Leave a comment

[ARTICLE] Design and Preliminary Feasibility Study of a Soft Robotic Glove for Hand Function Assistance in Stroke Survivors – Full Text

Various robotic exoskeletons have been proposed for hand function assistance during activities of daily living (ADL) of stroke survivors. However, traditional exoskeletons involve the use of complex rigid systems that impede the natural movement of joints, and thus reduce the wearability and cause discomfort to the user. The objective of this paper is to design and evaluate a soft robotic glove that is able to provide hand function assistance using fabric-reinforced soft pneumatic actuators. These actuators are made of silicone rubber which has an elastic modulus similar to human tissues. Thus, they are intrinsically soft and compliant. Upon air pressurization, they are able to support finger range of motion (ROM) and generate the desired actuation of the finger joints. In this work, the soft actuators were characterized in terms of their blocked tip force, normal and frictional grip force outputs. Combining the soft actuators and flexible textile materials, a soft robotic glove was developed for grasping assistance during ADL for stroke survivors. The glove was evaluated on five healthy participants for its assisted ROM and grip strength. Pilot test was performed in two stroke survivors to evaluate the efficacy of the glove in assisting functional grasping activities. Our results demonstrated that the actuators designed in this study could generate desired force output at a low air pressure. The glove had a high kinematic transparency and did not affect the active ROM of the finger joints when it was being worn by the participants. With the assistance of the glove, the participants were able to perform grasping actions with sufficient assisted ROM and grip strength, without any voluntary effort. Additionally, pilot test on stroke survivors demonstrated that the patient’s grasping performance improved with the presence and assistance of the glove. Patient feedback questionnaires also showed high level of patient satisfaction and comfort. In conclusion, this paper has demonstrated the possibility of using soft wearable exoskeletons that are more wearable, lightweight, and suitable to be used on a daily basis for hand function assistance of stroke survivors during activities of daily living.


The ability to perform basic activities of daily living (ADL) impacts a person’s quality of life and independence (Katz, 1983Andersen et al., 2004). However, an individual’s independence to perform ADLs is jeopardized due to hand motor impairments, which can be observed in patients with neurological disorders such as stroke. In order to improve hand motor functions in terms of strength and range of motion (ROM) (Kutner et al., 2010), stroke survivors undergo rehabilitation programs comprising repetitive practice of simulated ADL tasks (Michaelsen et al., 2006). Normally, patients undergo rehabilitation exercises in a specialized rehabilitation center under the guidance of physiotherapists or occupational therapists. However, due to increasing patient population, it is foreseen that there will be a shortage of physiotherapists to assist in the rehabilitative process. Thus, there will be comparatively less therapy time, which will eventually lead to a slower recovery process for the patients. Over the past decade, technological developments in robotics have facilitated the rehabilitative process and have shown potential to assist patients in their daily life (Maciejasz et al., 2014). One example of such a device is the hand exoskeleton, which is secured around the hand to guide and assist the movement of the encompassed joints. However, due to the complexity of the hand, designing a hand exoskeleton remains a challenging task.

Traditional hand exoskeletons involve the use of rigid linkage-based mechanisms. In this kind of mechanism, rigid components, such as linear actuators, rotary motors, racks, and pinions as well as rigid linkages are normally involved (Worsnopp et al., 2007Rotella et al., 2009Martinez et al., 2010). To assist hand movements that have high degrees of freedom (DOFs), traditional exoskeletons can be incorporated with a substantial number of actuators to achieve the requirement. However, this means that their application is limited due to the increasing bulkiness for higher DOFs. Therefore, these devices are normally restricted in clinical settings and not suitable for performing home therapy. Additionally, their rigidity, weight and constraint on the non-actuated DOFs of the joints pose complications. As a result, the level of comfort and safety of patients is reduced. In view of this, there is an apparent need for the development of exoskeletons that may be used in both clinical and home settings. A lightweight and wearable exoskeleton may allow patients to bring back home to continue daily therapy or to serve as an assistive device for the ADLs.

The development of wearable robotic exoskeletons serves to provide an alternative approach toward addressing this need. Instead of using rigid linkage as an interface between the hand and the actuators, wearable exoskeletons typically utilize flexible materials such as fabric (Sasaki et al., 2004Yap et al., 2016a) and polymer (Kang et al., 2016), driven by compliant actuators such as cables (Sangwook et al., 2014Xiloyannis et al., 2016) and soft inflatable actuators (Polygerinos et al., 2015dYap et al., 2016c). Therefore, they are more compliant and lightweight compared to the rigid linkage-based mechanism. Cable-driven based exoskeletons involve the use of cables that are connected to actuators in the form of electrical motors situated away from the hand (Nilsson et al., 2012Ying and Agrawal, 2012Sangwook et al., 2014Varalta et al., 2014). By providing actuations on both dorsal and palmar sides of the hand, bi-directional cable-driven movements are possible (Kang et al., 2016). These cables mimic the capability of the tendons of the human hand and they are able to transmit the required pulling force to induce finger flexion and extension. However, the friction of the cable, derailment of the tendon, and inaccurate routing of the cable due to different hand dimensions can affect the efficiency of force transmission in the system.

On the other hand, examples of the soft inflatable actuators are McKibben type muscles (Feifei et al., 2006Tadano et al., 2010), sheet-like rubber muscles (Sasaki et al., 2004Kadowaki et al., 2011), and soft elastomeric actuators (Polygerinos et al., 2015b,cYap et al., 2015); amongst which, soft elastomeric actuators have drawn increasing research interest due to their high compliance (Martinez et al., 2013). This approach typically embeds pneumatic chamber networks in elastomeric constructs to achieve different desired motions with pressurized air or water (Martinez et al., 2012). Soft elastomeric actuators are highly customizable. They are able to achieve multiple DOFs and complex motions with a single input, such as fluid pressurization. The design of a wearable hand exoskeleton that utilizes soft elastomeric actuators is usually simple and does not require precise routing for actuation, compared to the cable-driven mechanism. Thus, the design reduces the possibility of misalignment and the setup time. These properties allow the development of hand exoskeletons that are more compliant and wearable, with the ability to provide safe human-robot interaction. Additionally, several studies have demonstrated that compactness and ease of use of an assistive device critically affect its user acceptance (Scherer et al., 20052007). Thus, these exoskeletons provide a greater chance of user acceptance.

Table 1 summarizes the-state-of-art of soft robotic assistive glove driven by inflatable actuators. Several pioneer studies on inflatable assistive glove have been conducted by Sasaki et al. (2004)Kadowaki et al. (2011) and Polygerinos et al. (2015a,b,c). Sasaki et al. have developed a pneumatically actuated power assist glove that utilizes sheet-like curved rubber muscle for hand grasping applications. Polygerinos et al. have designed a hydraulically actuated grip glove that utilizes fiber-reinforced elastomeric actuators that can be mechanically programmed to generate complex motion paths similar to the kinematics of the human finger and thumb. Fiber reinforcement has been proved to be an effective method to constrain the undesired radial expansion of the actuators that does not contribute to effective motion during pressurization. However, this method limits the bending capability of the actuators (Figure S1); as a result, higher pressure is needed to achieve desired bending.

Table 1. Hand assistive exoskeletons driven by inflatable actuators.

Continue —> Frontiers | Design and Preliminary Feasibility Study of a Soft Robotic Glove for Hand Function Assistance in Stroke Survivors | Neuroscience

Figure 1. (A) A fabric-reinforced soft actuators with a corrugated fabric layer and an elastic fabric later [Actuator thickness, T = 12 mm, and length, L = 160 mm (Thumb), 170 mm (Little Finger), 180 mm (Index & Ring Fingers), 185 mm (Middle Finger)]. (B) Upon air pressurization, the corrugated fabric layer unfolds and expands due to the inflation of the embedded pneumatic chamber. Radial budging is constrained when the corrugated fabric layer unfolds fully. The elastic fabric elongates during air pressurization and stores elastic energy. The actuator achieves bending and extending motions at the same time. (C) A bending motion is preferred at the finger joints (II, IV, VI). An extending motion is preferred over the bending motion at the finger segments (I, III, V) and the opisthenar (VII).

, , , ,

Leave a comment

[ARTICLE] On neuromechanical approaches for the study of biological and robotic grasp and manipulation – Full Text


Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank and open-minded assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas at the interface of neuromechanics, neuroscience, rehabilitation and robotics.


Grasp and manipulation have captivated the imagination and interest of thinkers of all stripes over the millennia; and with enough reverence to even attribute the intellectual evolution of humans to the capabilities of the hand [123]. Simply put, manipulation function is one of the key elements of our identity as a species (for an overview, see [4]). This is a natural response to the fact that much of our physical and cognitive ability and well-being is intimately tied to the use of our hands. Importantly, we have shaped our tools and environment to match its capabilities (straightforward examples include lever handles, frets in string instruments, and touch-screens). This co-evolution between hand-and-world reinforces the notion that our hands are truly amazing and robust manipulators, as well as rich sensory, perceptual and even social information.

It then comes as no surprise that engineers and physicians have long sought to replicate and restore this functionality in machines—both as appendages to robots and prostheses attached to humans with missing upper limbs [5]. Robotic hands and prostheses have a long and illustrious history, with records of sophisticated articulated hands as early as Gottfried ‘Götz’ von Berlichingen’s iron hand in 1504 [6]. Other efforts [7891011] were often fueled by the injuries of war [12131415] and the Industrial Revolution [16]. The higher survival rate in soldiers who lose upper limbs [1718] and the continual emergence of artificial intelligence [1920] are but the latest impetus. Thus, the past 20 years have seen an explosion in designs, fueled by large scale governmental funding (e.g., DARPA’s Revolutionizing Prosthetics and HAPTIX projects, EU’s INPUT and SOFTPRO projects) and private efforts such as DeepMind. A new player in this space is the potentially revolutionary social network of high-quality amateur scientists as exemplified by the FABLAB movement [21]. They are enabled by ubiquitously accessible and inexpensive 3D printing and additive manufacturing tools [22], collaborative design databases ( and others), and communities with formal journals ( and Grassroots communities have also emerged that can, for example, compare and contrast the functionality of prosthetic hands whose price differs by three orders of magnitude (

For all the progress that we have seen, however, (i) robotic platforms remain best at pre-sorted, pick-and-place assembly tasks [23]; and (ii) many prosthetic users still prefer simple designs like the revered whole- or split-hook designs originally developed centuries ago [2425].

Why have robotic and prosthetic hands not come of age? This short review provides a current attempt to tackle this long-standing question in response to the current technological boom in robotic and prosthetic limbs. Similar booms occurred in response to upper limb injuries [25] after the Napoleonic [26], First [12] and Second World Wars [8], and—with the advent of powerful inexpensive computers—in response to industrial and space exploration needs in the 1960’s, 1970’s and 1980’s [272829303132]. We argue that a truly bio-inspired approach suffers, by definition, from both gaps in our understanding of the biology, and technical challenges in mimicking (what we understand of) biological sensors, motors and controllers. Although biomimicry is often not the ultimate goal in robotics in general, it is relevant for humanoids and prostheses. Thus, our approach is to clarify when and why a better understanding of the biology of grasp and manipulation would benefit robotic grasping and manipulation.

Similarly, why is our understanding of the nature, function and rehabilitation of biological arms and hands incomplete? Jacob Benignus Winsløw Jacques-Bénigne Winslow, (1669—1760) noted in his Exposition anatomique de la structure du corps humain (1732) that ‘The coordination of the muscles of the live hand will never be understood’ [33]. Interestingly, he is still mostly correct. As commented in detail before [4], there has been much work devoted to inferring the anatomical, physiological, neural and cognitive processes that produce the upper limb function we so dearly appreciate and passionately work to restore following trauma or pathology. We argue, as Galileo Galilei did, that mathematics and engineering have much to contribute to the understanding of biological systems. Without such a ‘mathematical language’ we run the risk, as Galileo put it, of ‘wandering in vain through a dark labyrinth’ [34]. Thus, this short review also attempts to point out important mathematical and engineering developments and advances that have helped our understanding of our hands.

This review first contrasts the fundamental differences between engineering and neuroscience approaches to biological robotic systems. Whereas the former applies engineering principles, the latter relies on scientific inference. We then discuss how the physics of the world provides a common ground between them because both types of systems have similar functional goals, and must abide by the same physical laws. We go on to evaluate how biological and robotic systems implement the necessary sensory and motor functions using the dramatically different anatomy, morphology and mechanisms available to each. This inevitably raises questions about differences in their sensorimotor control strategies. Whereas engineering system can be designed and manufactured to optimize well-defined functional features, biological systems evolve without such strict tautology. Biological systems likely evolve by implementing ecologically and temporally good-enough, sub-optimal or habitual control strategies in response to the current multi-dimensional functional constraints and goals in the presence of competition, variability, uncertainty, and noise. We conclude by exploring the notion that the functional versatility of biological systems that roboticists admire is, in fact, enabled by the very nonlinearities and complexities in anatomy, sensorimotor physiology, and neural function that engineering approaches often seek to avoid. […]

Continue —> On neuromechanical approaches for the study of biological and robotic grasp and manipulation | Journal of NeuroEngineering and Rehabilitation | Full Text

, , , ,

Leave a comment

[BOOK] Virtual Reality Enhanced Robotic Systems for Disability Rehabilitation – Google Books

Virtual Reality Enhanced Robotic Systems for Disability Rehabilitation

Front Cover
Hu, Fei
IGI GlobalJan 7, 2016 – Technology & Engineering – 383 pages

The study of technology and its implications in the medical field has become an increasingly crucial area of research. By integrating technological innovations into clinical practices, patients can receive improved diagnoses and treatments, as well as faster and safer recoveries.

Virtual Reality Enhanced Robotic Systems for Disability Rehabilitation is an authoritative reference source for the latest scholarly research on the use of computer-assisted rehabilitation methods for disabled patients. Highlighting the application of robots, sensors, and virtual environments, this book is ideally designed for graduate students, engineers, technicians, and company administrators interested in the incorporation of auto-training methods in patient recovery.

Source: Virtual Reality Enhanced Robotic Systems for Disability Rehabilitation – Google Books

, , , ,

Leave a comment

%d bloggers like this: