Posts Tagged robot

[Abstract] Physiological Responses and Perceived Exertion During Robot-Assisted and Body Weight–Supported Gait After Stroke

Introduction. Physiological responses are rarely considered during walking after stroke and if considered, only during a short period (3-6 minutes). The aims of this study were to examine physiological responses during 30-minute robot-assisted and body weight–supported treadmill and overground walking and compare intensities with exercise guidelines.

Methods. A total of 14 ambulatory stroke survivors (age: 61 ± 9 years; time after stroke: 2.8 ± 2.8 months) participated in 3 separate randomized walking trials. Patients walked overground, on a treadmill, and in the Lokomat (60% robotic guidance) for 30 minutes at matched speeds (2.0 ± 0.5 km/h) and matched levels of body weight support (BWS; 41% ± 16%). Breath-by-breath gas analysis, heart rate, and perceived exertion were assessed continuously.

Results. Net oxygen consumption, net carbon dioxide production, net heart rate, and net minute ventilation were about half as high during robot-assisted gait as during body weight–supported treadmill and overground walking (P < .05). Net minute ventilation, net breathing frequency, and net perceived exertion significantly increased between 6 and 30 minutes (respectively, 1.8 L/min, 2 breaths/min, and 3.8 units). During Lokomat walking, exercise intensity was significantly below exercise recommendations; during body weight–supported overground and treadmill walking, minimum thresholds were reached (except for percentage of heart rate reserve during treadmill walking).

Conclusion. In ambulatory stroke survivors, the oxygen and cardiorespiratory demand during robot-assisted gait at constant workload are considerably lower than during overground and treadmill walking at matched speeds and levels of body weight support. Future studies should examine how robotic devices can be Future studies should examine how robotic devices can be exploited to induce aerobic exercise.

 

via Physiological Responses and Perceived Exertion During Robot-Assisted and Body Weight–Supported Gait After Stroke – Nina Lefeber, Emma De Keersmaecker, Stieven Henderix, Marc Michielsen, Eric Kerckhofs, Eva Swinnen, 2018

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[WEB SITE] RATULS Trial Using BIONIK InMotion Researches Robot-Assisted Stroke Therapy

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A landmark Robot Assisted Training for the Upper Limb after Stroke (RATULS) trial utilizing BIONIK Laboratories Corp’s InMotion Robotic Therapy Systems was completed recently, the Toronto-based company announces.

The RATULS trial, which began in 2014 and was completed at the end of 2018, compared the clinical effectiveness of robot-assisted training, enhanced upper limb therapy, and usual care for patients with moderate or severe upper limb functional limitation.

Results were presented recently at the European Stroke Organisation Conference (ESOC) in Milan, Italy, and published in The Lancet.

“We are pleased that the RATULS trial confirmed the finding of previous research studies which demonstrated that robot-assisted therapy improved upper limb impairment when compared with conventional care methods for stroke victims.

“The trial’s finding that robotic therapy is the only therapy to statistically maintain a significant impairment advantage at six months after treatment is a strong signal that robotic therapy is critical for achieving positive patient outcomes,” says Dr Eric Dusseux, CEO, BIONIK Laboratories, in a media release.

For the RATULS trial, the primary outcome for upper limb success was determined by Action Research Arm Test (ARAT), with four distinct success criteria that varied according to baseline severity, not used previously and developed by the RATULS trial team.

Although the findings demonstrated that robot-assisted therapy improved upper limb impairment, using this ARAT measurement, the trial was unable to conclude that robot-assisted therapy or enhanced upper limb therapy resulted in improved upper limb functionality after stroke compared with usual care provided to patients with stroke-related upper limb functional limitation. The attrition rate was also drastically reduced in patient population following either robotic therapy or enhanced upper limb therapy versus usual care only, and most of the withdrawals before 3 months in usual care were due to disappointment with treatment allocation, the release explains.

“The combination of evidenced-based medicine and real-world clinical feedback have led to the release of substantially improved versions of the InMotion ARM Robotic Therapy System announced in early 2018, and the InMotion ARM/HAND Robotic Therapy System announced beginning of 2019. These versions of our products include enhanced software applications with patient-centric configurable protocols to assist the therapist in providing specialized treatment of stroke and traumatic brain injury.”

[Source(s): BIONIK Laboratories Corp, Business Wire]

 

via RATULS Trial Using BIONIK InMotion Researches Robot-Assisted Stroke Therapy – Rehab Managment

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[Abstract] Control and Dynamic Manipulability of a Dual-Arm/Hand Robotic Exoskeleton System (EXO-UL8) for Rehabilitation Training in Virtual Reality

Author & Article Info

Every year there are about 800,000 new stroke patients in the US, and many of them suffer from upper limb neuromuscular disabilities including but not limited to: weakness, spasticity and abnormal synergy. Patients usually have the potential to rehabilitate (to some extent) based on neuroplasticity, and physical therapy intervention helps accelerate the recovery. However, many patients could not afford the expensive physical therapy after the onset of stroke, and miss the opportunity to get recovered. Robot-assisted rehabilitation thus might be the solution, with the following unparalleled advantages:

  1. 24/7 capability of human arm gravity compensation;
  2. multi-joint movement coordination/correction, which could not be easily done by human physical therapists;
  3. dual-arm training, either coupled in joint space or task space;
  4. quantitative platform for giving instructions, providing assistance, exerting resistance, and collecting real-time data in kinematics, dynamics and biomechanics;
  5. potential training protocol personalization; etc.

However, in the rehabilitation robotics field, there are still many open problems. I am especially interested in:

  1. compliant control, in high-dimensional multi-joint coordination condition;
  2. assist-as-needed (AAN) control, in quantitative model-based approach and model-free approach;
  3. dual-arm training, in both symmetric and asymmetric modes;
  4. system integration, e.g., virtual reality (VR) serious games and graphical user interfaces (GUIs) design and development.

Our dual-arm/hand robotic exoskeleton system, EXO-UL8, is in its 4th generation, with seven (7) arm degrees-of-freedom (DOFs) and one (1) DOF hand gripper enabling hand opening and closing on each side. While developing features on this research platform, I contributed to the robotics research field in the following aspects:

(1) I designed and developed a series of eighteen (18) serious VR games and GUIs that could be used for interactive post-stroke rehabilitation training. The VR environment, together with the exoskeleton robot, provides patients and physical therapists a quantitative rehabilitation training platform with capability in real-time human performance data collection and analysis.

(2) To provide better compliant control, my colleagues and I proposed and implemented two new admittance controllers, based on the work done by previous research group alumni. Both the hyper parameter-based and Kalman Filter-based admittance controllers have satisfactory heuristic performance, and the latter is more promising in future adaptation. Unlike many other upper-limb exoskeletons, our current system utilizes force and torque (F/T) sensors and position encoders only, no surface electromyography (sEMG) signals are used. It brings convenience to practical use, as well as technical challenges.

(3) To provide better AAN control, which is still not well understood in the academia, I worked out a redundant version of modified dynamic manipulability ellipsoid (DME) model to propose an Arm Postural Stability Index (APSI) to quantify the difficulty heterogeneity of the 3D Cartesian workspace. The theoretical framework could be used to teach the exoskeleton where and when to provide assistance, and to guide the virtual reality where to add new minimal challenges to stroke patients. To the best of my knowledge, it is also for the first time that human arm redundancy resolution was investigated when arm gravity is considered.

(4) For the first time, my colleagues and I have done a pilot study on asymmetric dual-arm training using the exoskeleton system on one (1) post-stroke patient. The exoskeleton on the healthy side could trigger assistance for that on the affected side, and validates that the current mechanism/control is eligible for asymmetric dual-arm training.

(5) Other works of mine include: activities of daily living (ADLs) data visualization for VR game difficulty design; human arm synergy modeling; dual-arm manipulation taxonomy classification (on-going work).

via Control and Dynamic Manipulability of a Dual-Arm/Hand Robotic Exoskeleton System (EXO-UL8) for Rehabilitation Training in Virtual Reality

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[Abstract + References] eConHand: A Wearable Brain-Computer Interface System for Stroke Rehabilitation

Abstract

Brain-Computer Interface (BCI) combined with assistive robots has been developed as a promising method for stroke rehabilitation. However, most of the current studies are based on complex system setup, expensive and bulky devices. In this work, we designed a wearable Electroencephalography(EEG)-based BCI system for hand function rehabilitation of the stroke. The system consists of a customized EEG cap, a small-sized commercial amplifer and a lightweight hand exoskeleton. In addition, visualized interface was designed for easy use. Six healthy subjects and two stroke patients were recruited to validate the safety and effectiveness of our proposed system. Up to 79.38% averaged online BCI classification accuracy was achieved. This study is a proof of concept, suggesting potential clinical applications in outpatient environments.

2. E. Donchin , K. Spencer and R. Wijesinghe , “The mental prosthesis: assessing the speed of a P300-based brain-computer interface”, IEEE Transactions on Rehabilitation Engineering, vol. 8, no. 2, pp. 174-179, 2000.

3. D. McFarland and J. Wolpaw , “Brain-Computer Interface Operation of Robotic and Prosthetic Devices”, Computer, vol. 41, no. 10, pp. 52-56, 2008.

4. Xiaorong Gao , Dingfeng Xu , Ming Cheng and Shangkai Gao , “A bci-based environmental controller for the motion-disabled”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 11, no. 2, pp. 137-140, 2003.

5. A. Ramos-Murguialday , D. Broetz , M. Rea et al “Brain-machine interface in chronic stroke rehabilitation: A controlled study”, Annals of Neurology, vol. 74, no. 1, pp. 100-108, 2013.

6. F. Pichiorri , G. Morone , M. Petti et al “Brain-computer interface boosts motor imagery practice during stroke recovery”, Annals of Neurology, vol. 77, no. 5, pp. 851-865, 2015.

7. M. A. Cervera , S. R. Soekadar , J. Ushiba et al “Brain-computer interfaces for post-stroke motor rehabilitation: a meta-analysis”, Annals of Clinical and Translational Neurology, vol. 5, no. 5, pp. 651-663, 2018.

8. K. Ang , K. Chua , K. Phua et al “A Randomized Controlled Trial of EEG-Based Motor Imagery Brain-Computer Interface Robotic Rehabilitation for Stroke”, Clinical EEG and Neuroscience, vol. 46, no. 4, pp. 310-320, 2014.

9. N. Bhagat , A. Venkatakrishnan , B. Abibullaev et al “Design and Optimization of an EEG-Based Brain Machine Interface (BMI) to an Upper-Limb Exoskeleton for Stroke Survivors”, Frontiers in Neuroscience, vol. 10, pp. 122, 2016.

10. J. Webb , Z. G. Xiao , K. P. Aschenbrenner , G. Herrnstadt , and C. Menon , “Towards a portable assistive arm exoskeleton for stroke patient rehabilitation controlled through a brain computer interface”, in Biomedical Robotics and Biomechatronics (BioRob), 2012 4th IEEE RAS & EMBS International Conference, pp. 1299-1304, 2012.

11. A. L. Coffey , D. J. Leamy , and T. E. Ward , “A novel BCI-controlled pneumatic glove system for home-based neurorehabilitation”, in Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE, pp. 3622-3625, 2014.

12. D. Bundy , L. Souders , K. Baranyai et al “Contralesional Brain-Computer Interface Control of a Powered Exoskeleton for Motor Recovery in Chronic Stroke Survivors”, Stroke, vol. 48, no. 7, pp. 1908-1915, 2017.

13. X. Shu , S. Chen , L. Yao et al “Fast Recognition of BCI-Inefficient Users Using Physiological Features from EEG Signals: A Screening Study of Stroke Patients”, Frontiers in Neuroscience, vol. 12, pp. 93, 2018.

14. A. Delorme , T. Mullen , C. Kothe et al “EEGLAB, SIFT, NFT, BCILAB, and ERICA: New Tools for Advanced EEG Processing”, Computational Intelligence and Neuroscience, vol. 2011, pp. 1-12, 2011.

15. G. Schalk , D. McFarland , T. Hinterberger , N. Birbaumer and J. Wolpaw , “BCI2000: A General-Purpose Brain-Computer Interface (BCI) System”, IEEE Transactions on Biomedical Engineering, vol. 51, no. 6, pp. 1034-1043, 2004.

16. M. H. B. Azhar , A. Casey , and M. Sakel , “A cost-effective BCI assisted technology framework for neurorehabilitation”, The Seventh International Conference on Global Health Challenges, 18th-22nd November, 2018. (In Press)

17. C. M. McCrimmon , M. Wang , L. S. Lopes et al “A small, portable, battery-powered brain-computer interface system for motor rehabilitation”, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 2776-2779, 2016.

18. J. Meng , B. Edelman , J. Olsoe et al “A Study of the Effects of Electrode Number and Decoding Algorithm on Online EEG-Based BCI Behavioral Performance”, Frontiers in Neuroscience, vol. 12, pp. 227, 2018.

19. T. Mullen , C. Kothe , Y. Chi et al “Real-time neuroimaging and cognitive monitoring using wearable dry EEG”, IEEE Transactions on Biomedical Engineering, vol. 62, no. 11, pp. 2553-2567, 2015.

 

via eConHand: A Wearable Brain-Computer Interface System for Stroke Rehabilitation – IEEE Conference Publication

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[ARTICLE] Hand Rehabilitation Robotics on Poststroke Motor Recovery – Full Text

Abstract

The recovery of hand function is one of the most challenging topics in stroke rehabilitation. Although the robot-assisted therapy has got some good results in the latest decades, the development of hand rehabilitation robotics is left behind. Existing reviews of hand rehabilitation robotics focus either on the mechanical design on designers’ view or on the training paradigms on the clinicians’ view, while these two parts are interconnected and both important for designers and clinicians. In this review, we explore the current literature surrounding hand rehabilitation robots, to help designers make better choices among varied components and thus promoting the application of hand rehabilitation robots. An overview of hand rehabilitation robotics is provided in this paper firstly, to give a general view of the relationship between subjects, rehabilitation theories, hand rehabilitation robots, and its evaluation. Secondly, the state of the art hand rehabilitation robotics is introduced in detail according to the classification of the hardware system and the training paradigm. As a result, the discussion gives available arguments behind the classification and comprehensive overview of hand rehabilitation robotics.

1. Background

Stroke, caused by death of brain cells as a result of blockage of a blood vessel supplying the brain (ischemic stroke) or bleeding into or around the brain (hemorrhagic stroke), is a serious medical emergency []. Stroke can result in death or substantial neural damage and is a principal contributor to long-term disabilities []. According to the World Health Organization estimates, 15 million people suffer stroke worldwide each year []. Although technology advances in health care, the incidence of stroke is expected to rise over the next decades []. The expense on both caring and rehabilitation is enormous which reaches $34 billion per year in the US []. More than half of stroke survivors experience some level of lasting hemiparesis or hemiplegia resulting from the damage to neural tissues. These patients are not able to perform daily activities independently and thus have to rely on human assistance for basic activities of daily living (ADL) like feeding, self-care, and mobility [].

The human hands are very complex and versatile. Researches show that the relationship between the distal upper limb (i.e., hand) function and the ability to perform ADL is stronger than the other limbs []. The deficit in hand function would seriously impact the quality of patients’ life, which means more demand is needed on the hand motor recovery. However, although most patients get reasonable motor recovery of proximal upper extremity according to relevant research findings, recovery at distal upper extremity has been limited due to low effectivity []. There are two main reasons for challenges facing the recovery of the hand. First, in movement, the hand has more than 20 degree of freedom (DOF) which makes it flexible, thus being difficult for therapist or training devices to meet the needs of satiety and varied movements []. Second, in function, the area of cortex in correspondence with the hand is much larger than the other motor cortex, which means a considerable amount of flexibility in generating a variety of hand postures and in the control of the individual joints of the hand. However, to date, most researches have focused on the contrary, lacking of individuation in finger movements []. Better rehabilitation therapies are desperately needed.

Robot-assisted therapy for poststroke rehabilitation is a new kind of physical therapy, through which patients practice their paretic limb by resorting to or resisting the force offered by the robots []. For example, the MIT-Manus robot uses the massed training approach by practicing reaching movements to train the upper limbs []; the Mirror Image Movement Enabler (MIME) uses the bilateral training approach to train the paretic limb while reducing abnormal synergies []. Robot-assisted therapy has been greatly developed over the past three decades with the advances in robotic technology such as the exoskeleton and bioengineering, which has become a significant supplement to traditional physical therapy []. For example, compared with the therapist exhausted in training patients with manual labor, the hand exoskeleton designed by Wege et al. can move the fingers of patients dexterously and repeatedly []. Besides, some robots can also be controlled by a patient’s own intention extracted from biosignals such as electromyography (EMG) and electroencephalograph (EEG) signals []. These make it possible to form a closed-loop rehabilitation system with the robotic technology, which cannot be achieved by any conventional rehabilitation therapy [].

Existing reviews of hand rehabilitation robotics on poststroke motor recovery are insufficient, for most studies research on the application of robot-assisted therapy on other limbs instead of the hand []. Furthermore, current reviews focus on either the hardware design of the robots or the application of specific training paradigms [], while both of them are indispensable to an efficient hand rehabilitation robot. The hardware system makes the foundation of the robots’ function, while the training paradigm serves as the real functional parts in the motor recovery that decides the effect of rehabilitation training. These two parts are closely related to each other.

This paper focuses on the application of robot-assisted therapy on hand rehabilitation, giving an overview of hand rehabilitation robotics from the hardware systems to the training paradigms in current designs, for a comprehensive understanding is pretty meaningful to the development of an effective rehabilitation robotic system. The second section provides a general view of the robots in the entire rehabilitation robotic system. Then, the third section sums up and classifies hardware systems and the training paradigms in several crucial aspects on the author’s view. Last, the state of the art hand rehabilitation robotics is discussed and possible direction of future robotics in hand rehabilitation is predicted.[…]

Continue —-> Hand Rehabilitation Robotics on Poststroke Motor Recovery

 

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Figure 3
Examples of different kinds of robots [].

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[Abstract] Robot-Assisted Reach Training With an Active Assistant Protocol for Long-Term Upper Extremity Impairment Poststroke: A Randomized Controlled Trial.

Abstract

OBJECTIVE:

To assess whether robot-assisted reach training (RART) with an active assistant protocol can improve upper extremity function and kinematic performance in chronic stroke survivors.

DESIGN:

This study was conducted as a randomized controlled trial.

SETTING:

National rehabilitation center.

PARTICIPANTS:

Chronic stroke survivors (N=38) were randomized into 2 groups: a robot-assisted reach training with assist-as-needed (RT-AAN) group and a robot-assisted reach training with guidance force (RT-G) group.

INTERVENTION:

The RT-AAN group received robot-assisted reach training with an assist-as-needed mode for 40 minutes per day, 3 times per week over a 6-week period, and the RT-G group participated in the RART with a guidance mode for 40 minutes per day, 3 times per week over a 6-week period.

MAIN OUTCOME MEASURES:

Upper extremity functions were measured with Fugl-Meyer Assessment (FMA), Action Research Arm Test (ARAT), and Box and Block Test. In addition, movement velocities were measured as an index for upper extremity kinematic performances in 6 directions.

RESULTS:

Both groups showed significant improvements in FMA, ARAT, and kinematics (movement velocity) in all directions (targets 1-6, P<.05). However, the RT-AAN group showed significantly more improvement than the RT-G group in FMA and ARAT (P<.05).

CONCLUSIONS:

RART with an active assistant protocol showed improvements of upper extremity function and kinematic performance in chronic stroke survivors. In particular, assist-as-needed robot control was effective for upper extremity rehabilitation. Therefore robot-assisted training may be suggested as an effective intervention to improve upper extremity function in chronic stroke survivors.

 

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[ARTICLE] Design of a robot-assisted exoskeleton for passive wrist and forearm rehabilitation – Full Text

Abstract

This paper presents a new exoskeleton design for wrist and forearm rehabilitation. The contribution of this study is to offer a methodology which shows how to adapt a serial manipulator that reduces the number of actuators used on exoskeleton design for the rehabilitation. The system offered is a combination of end-effector- and exoskeleton-based devices. The passive exoskeleton is attached to the end effector of the manipulator, which provides motion for the purpose of rehabilitation process. The Denso VP 6-Axis Articulated Robot is used to control motion of the exoskeleton during the rehabilitation process. The exoskeleton is designed to be used for both wrist and forearm motions. The desired moving capabilities of the exoskeleton are flexion–extension (FE) and adduction–abduction (AA) motions for the wrist and pronation–supination (PS) motion for the forearm. The anatomical structure of a human limb is taken as a constraint during the design. The joints on the exoskeleton can be locked or unlocked manually in order to restrict or enable the movements. The parts of the exoskeleton include mechanical stoppers to prevent the excessive motion. One passive degree of freedom (DOF) is added in order to prevent misalignment problems between the axes of FE and AA motions. Kinematic feedback of the experiments is performed by using a wireless motion tracker assembled on the exoskeleton. The results proved that motion transmission from robot to exoskeleton is satisfactorily achieved. Instead of different exoskeletons in which each axis is driven and controlled separately, one serial robot with adaptable passive exoskeletons is adequate to facilitate rehabilitation exercises.

 

Introduction

Deficiencies in the upper extremities restrain a person’s ability to go about daily life, consequently limiting one’s independence. Therefore, robots are used to perform task-oriented repetitive movements in order to improve motor recovery, muscle strength and movement coordination. Stroke is one of the primary reasons for a decrease in motor function of the upper limbs of human beings. It restricts the daily, social and household activities of the patients. Therefore, rehabilitation therapy is required to recover some of the movement lost (Bayona et al., 2005; Bonita and Beaglehole, 1988; Cramer and Riley, 2008). This is accomplished by a long-term intensive and repetitive rehabilitation period. Traditional therapies not only require great effort but also require the manual assistance of physiotherapists. The one-to-one contact of the therapists with their patients leaves the therapists exhausted. Moreover, therapists have limited abilities with regard to speed, senses, strength, and repeatability.

Robot-aided therapy is a developing part of post-stroke rehabilitation care (Reinkensmeyer et al., 2004). Robotic rehabilitation systems ensure compact therapy which can be applied in repetitive, controllable and accurate manner (Kahn et al., 2006; Marchal-Crespo and Reinkensmeyer, 2009). Robotic devices can provide limitless repeatability for patients thus decreasing the effort that therapists have to make (Kwakkel et al., 2008; Lum et al., 2002). Additionally, patient performance evaluation can easily be monitored and assessed by the therapists to adjust the rest of the required therapy (Celik et al., 2010; Ponomarenko et al., 2014).

The types of exercises are grouped into two branches: active and passive exercises. The subjects move their limbs actively and apply torque and/or force in active exercises. Passive exercises are in contrast to active exercises, in which the subjects remain passive during the exercise while an active device moves the limb. Continuous passive motion (CPM) is generated in this way (Maciejasz et al., 2014).

There is a broad range of robotic systems presented for upper-extremity rehabilitation. The mechanical structure of the rehabilitation robots can be mainly grouped into two parts: “end-effector-based” and “exoskeletons”. MIT-MANUS (Krebs et al., 1998) and MIME (Lum et al., 2002) are included in the first part. End-effector-type robots cover a large workspace without having the capability to apply torques to specific joints of the arm. Having simpler control structure than exoskeletons is an advantage of end-effector-type devices. The most distal part of the robot is in contact with the patient limb. The segments of the upper extremities can be regarded as a mechanical chain. Therefore, motion in the end effector of the robot will automatically move other segments of the patient. They may cause redundant configurations of the patient’s upper extremities and may risk injury. Exoskeletons are the external structural mechanisms that have joints and links that can collaborate with the human body. They transmit motion exerted by the links to the human joints, thus making them suitable for the human anatomy. Exoskeletons must be able to carry out movements within the natural limitations of a human wrist for an ergonomic design. Mechanical and control issues are more complex than end-effector-type devices. The 5 degrees of freedom (DOF) MAHI (Gupta and O’Malley, 2006), 6 DOF ARMin (Nef et al., 2008) and 7 DOF CADEN-7 (Perry et al., 2007) are some examples of exoskeletons used in upper-extremity rehabilitation. LIMPACT (Otten et al., 2015), MIT-Manus (Krebs et al., 1998) and MIME (Lum et al., 2005) are prime examples of systems designed for assisting upper-limb proximal joints (the shoulder and the elbow). On the other hand, CR-2 Haptic (Khor et al., 2014) has one rotational DOF. There are manual reconfigurations for any specific wrist movement. Systems called Universal Haptic Drive (Oblak et al., 2010), Bi-Manu-Track (Lum et al., 1993) and Supinator Extender (Allington et al., 2011) have 2 DOF. The closest configuration resembling a human wrist and a rehabilitation robot can be employed by a 3 DOF system with three revolute joints. This configuration type enhances the functionality of devices providing rehabilitation services as it allows independence for specific motions of the wrist. RiceWrist (Gupta et al., 2008) and CRAMER (Spencer et al., 2008) use parallel mechanisms for wrist and forearm rehabilitation. RiceWrist-S (Pehlivan et al., 2012) is a 3 DOF exoskeleton system which is the developed version of RiceWrist (Gupta et al., 2008). A three-axis gimbal called WristGimbal (Martinez et al., 2013) offers flexibility to adjust rotation centers of the axes in order to match the wrist center of the patient. A 3 DOF self-aligning exoskeleton given in Beekhuis et al. (2013) compensates for misalignment of the wrist and forearm. Parallelogram linkages are used for this purpose. Nu-Wrist (Omarkulov et al., 2016) is a novel self-aligning 3 DOF system allowing passive adaptation in the wrist joint.

This paper presents the design of an exoskeleton for human wrist and forearm rehabilitation. Specific wrist and forearm therapies are performed. An issue with the angular displacement limit of a robot axis was experienced. The solution method obtained by changing the design is given herein. Adapting a 6 DOF Denso robot for wrist and forearm rehabilitation is proposed. The novelty of the study is the use of an exoskeleton driven by a serial robot, which is a method that has not yet been tackled in the literature. The proposed system hybridized the end-effector-type and exoskeleton-type rehabilitation systems in order to utilize advantages and to avoid disadvantages. Precise movement transmission from robot to patient limb can be provided by using an exoskeleton which plays a guide role in the exercises. This adaptation makes the system feasible to apply torques to specific joints of the wrist and allow independent, concurrent and precise movement control. This technique offers flexibility to the users. If the user wants wrist and forearm rehabilitation, a 3-D model of the exoskeleton is designed, manufactured with 3-D printing technology and interfaced with the robot. The exoskeleton may be designed for ankle, shoulder and/or elbow applications. Therefore, a serial robot can be used as a motion provider for different types of rehabilitation. Instead of different exoskeletons having a motor for each axis, the combination of a serial robot and passive exoskeleton is enough to perform the rehabilitation exercises.

Wrist and forearm motion and exoskeleton design

A human uses the distal parts of his/her arm (i.e., wrist, forearm) in coordination with proximal parts (i.e., elbow, shoulder) in order to carry out movements required in daily life, e.g., wrist and forearm motions such as eating, writing, opening a door, driving an automobile and so on. The wrist joint has got 2 DOF; flexion and extension (FE) and radial–ulnar deviation. Radial–ulnar deviations can also be called adduction and abduction (AA), respectively. Flexion is the bending of the wrist so that the palm approaches the anterior surface of the forearm. The extension is the reverse of flexion. Abduction (radial deviation) is the bending of the wrist towards to the thumb side. The reverse of this motion is called adduction (ulnar deviation). Pronation and supination (PS) are the movements for the forearm. Pronation is applied to a hand such that the palm turns backward or downward. Supination is the rotation of the forearm such that the palm of the hand faces anteriorly to the anatomic position (Omarkulov et al., 2016). These motions are given in Fig. 1.

https://www.mech-sci.net/10/107/2019/ms-10-107-2019-f01

Figure 1DOF of wrist and forearm (Omarkulov et al., 2016).

[…]

 

Continue —> MS – Design of a robot-assisted exoskeleton for passive wrist and forearm rehabilitation

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[VIDEO] Watch a robotic exoskeleton help a stroke patient walk – YouTube

Although it’s a far cry from the exosuits of science fiction, researchers have developed a robotic exoskeleton that can help stroke victims regain use of their legs. Nine out of 10 stroke patients are afflicted with partial paralysis, leaving some with an abnormal gait. The exosuit works by pulling cords attached to a shoe insole, providing torque to the ankle and correcting the abnormal walking motion. With the suit providing assistance to their joints, the stroke victims are able to maintain their balance, and walk similarly to the way they had prior to their paralysis, the team reports today in Science Translational Medicine. The exosuit is an adaptation of a previous design developed for the Defense Advanced Research Projects Agency Warrior Web program, a Department of Defense plan to develop assistive exosuits for military applications. Although similar mechanical devices have been built in the past to assist in gait therapy, these were bulky and had to be kept tethered to a power source. This new suit is light enough that with a decent battery, it could be used to help patients walk over terrain as well, not just on a treadmill. The researchers say that although the technology needs long-term testing, it could start to decrease the time it takes for stroke patients to recover in the near future.

via Watch a robotic exoskeleton help a stroke patient walk | Science | AAAS

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[WEB SITE] Robots and the Future of Disability and Accessible Technology – Videos

Will We Be Cyborgs? Robots and the Future of Disability

Robots are in the news a lot these days, especially robots for people with disabilities. In Japan, a recently-opened café hired people with disabilities to operate robotic servers that take orders and bring food. The futuristic dining experience brings in customers while also providing valuable jobs to people who would otherwise be unemployed.

When I heard about this café, I was reminded of the movie “Surrogates,” in which humans live their lives through robotic bodies that were originally developed for people with disabilities. The film presents a dystopian view of such a world, depicting most people eschewing their physical bodies for a “safe” robotic existence. (Spoiler alert!) The villain was angered when able-bodied people started using the technology and sought to destroy it to force people to connect in the “real world” again. The film ends with this goal achieved, many lives saved and the people with disabilities who needed the technology forgotten and isolated again.

Could Robots Bring Us Closer Together?

If the plethora of “robots gone bad” movies is any indication, humans tend to fear that relying on robots or connecting to robots separates us further from each other. On one level I share those concerns, but what about the people who are currently excluded from various aspects of society because they aren’t able to physically interact in the same way as others? The cafe robots open new opportunities for physically disabled people to do a job most of us would otherwise be unable to perform. They also allow their operators to care for others, which has both practical and emotional significance for people who have needed more physical care than they could give in return. Robots could enable not just independence, but interdependence. Under the control of a person with a disability, a robot might not only help them dress but cook their spouse’s favorite meal and set the table for a romantic evening.

Unfortunately, the concept of a person with a disability controlling their robot and its actions is largely absent from most of the “care bots” currently being developed. Instead, they are designed to operate independently and offer activities such as social interaction, as well as health checks and reminders. It’s great that these technologies (as well as devices many of us already have in our homes like Siri and Alexa) can help with medication reminders and be used to call for help if someone falls or becomes ill. However, there is a line between empowerment and control, and it’s already been crossed in some disturbing ways. For example, there’s an FDA-approved pill that sends a digital alert to the patient’s doctor after it has been taken, and many sleep apneadevices monitor how long they’ve been used. People who don’t meet certain requirements face a loss of insurance coverage, even if there was a perfectly reasonable explanation for not using the technology. In the United States, a new law mandating electronic visit verification has been used in some states to GPS track people with disabilities and our caregivers, sending up alerts if the caregiver checks in at a “non-approved” location.

A subplot in the TV show “Humans,” which depicts a world with humanoid robots known as synths, takes this kind of surveillance to its terrifying but logical conclusion. An elderly man is told he must trade in his aging but beloved synthetic caregiver for a new model, as both are paid for by Britain’s National Health Service. When he asks the new model to cook his favorite meal, the robot refuses, stating that the fat and salt content exceed his doctor’s recommendations. In various creepy scenes, the robot controls his actions and restricts his life on the grounds of it being for his own good. To me, this storyline was more terrifying than any “Terminator” movie, because I already see the signs it could become reality for millions of seniors and people with disabilities.

Sex Robots Aren’t the Answer

Many robot development projects seem to focus on companionship, the idea that people with disabilities are lonely. They try to develop robots who act like people, instead of looking at the reasons why non-disabled humans aren’t including disabled humans. Concerns about loneliness and disability also inevitably come up when people start talking about sex robots. There are articles that express concern sex robots will further isolate humans from each other and give them unrealistic expectations for a human partner, but they’re far too quick to throw these worries out the window when it comes to people with disabilities. They’ll say things like “sex robots are mostly bad, but we need them for people with disabilities.” This implies people with disabilities can’t have a “normal” relationship, which is both inaccurate and offensive. No human would want us, so we should just settle for a robot?

To be clear, there’s a real need for more accessible sex toys and for technology to enable people with disabilities to enjoy sex regardless of physical limitations. However, many of the barriers people with disabilities face when it comes to healthy sexuality and relationships are not physical. They are social and cultural. While no individual is entitled to a relationship with another individual, people with disabilities as a group have the right to be seen as appealing potential partners, and to be judged on our personal merits, not our disabilities. The solution to loneliness among people with disabilities is to fight the stereotypes that lead to people not wanting to hire us, befriend us and date us, not create an artificial human that would do all those things but without any real emotion. That’s why I believe the real danger of AI isn’t Skynet-style world domination, but that society will make judgments about who is worthy of real human interaction and who isn’t.

Will We Be Cyborgs?

I believe it’s essential for people with disabilities to get involved with the development of new robotic technology, so it can be built “by us, for us” and empower us to be full participants in society. I’ve long been fascinated by Hugh Herr, a mountain climber turned MIT professor doing pioneering work in robotics and cybernetics. Herr lost both of his lower legs due to frostbite after a climbing accident but was determined to return to the sport he loved. After years of not caring much about school, he enrolled in college and began designing his own prosthetic legs, which he found actually gave him an advantage as he could change his feet to adapt to various terrains. Today, he develops advanced bionic limbs and is doing pioneering research in cybernetics.

Herr and his team recently created a cyborg. That word may bring up terrifying visions of alien hordes coming to “assimilate” humanity, but in our reality, he gave an amputee his leg back. The new technology maps a prosthetic leg’s movement to the nerves in what remains of the amputee’s leg, so his new foot moves just like his old one did — without him having to think about it. This is mind-blowing stuff. The team is also developing exoskeletons which could enable people with muscle weakness to walk and enhance the strength of able-bodied people. I wonder if such technology could eventually “unscramble” the incorrect neural signals of people like me who have brain damage from cerebral palsy or a stroke, enabling us to walk with an exoskeleton.

An End to Disability?

Some might be put off by Herr’s goal of an “end to disability,” and I also have concerns with that wording. Disability is part of being human, and people with disabilities will probably always exist, even if or when science finds a cure for certain diseases. Disability isn’t inherently bad, and the way society treats us often limits us more than our conditions.

But the “end” Herr proposes is vastly different from technologies like genetic engineering that would eradicate disability through erasure. Bionic technology validates the humanity of people with disabilities, views us as deserving of inclusion in society, and can transform us while retaining our uniqueness. It preserves our agency and gives us the opportunity to not only exist on a physically equal playing field, but a more advanced one. Bionic bodies will be able to move in ways those who are purely organic cannot. In the future, we may see dances that can only be performed with prosthetic limbs, bionic sports teams and vehicles controlled by nerve impulses. Mechanical parts would be integrated into our self-concept, a process Herr calls “neurological embodiment.”

Would neurological embodiment cause us to lose our humanity? Herr doesn’t seem to think so, and I don’t either. As a wheelchair user, I experience neurological embodiment every day. Although I can’t control my wheelchair with nerve impulses, on a psychological level it feels like part of my body, an extension of my self. I’ve heard many other wheelchair users say the same thing.

My neurological embodiment was further enhanced when I became a cyborg myself — though I never thought of it that way until I watched Herr’s TED Talk. Several months ago I got a standing wheelchair, which helps me not only stand, but bend to reach items, elevate to sit at a bar table, and so much more. It’s an amazing piece of technology, like a cross between a Transformer and an exoskeleton on wheels. I knew it would help with practical matters, but I never expected how much it would change the way I relate to other people, and the way people see me. When I talk to people at eye level or get out on the dance floor, it feels more real, more natural. Nothing comes between us physically or psychologically, and I no longer feel like an outsider. It seems like people don’t notice my wheelchair as much, and when they do, their comments are positive. They see me as a person enabled by a cool piece of tech, not an object of pity.

Our Bodies, Our Choice

Sometimes my wheelchair moves in a way that feels natural, but other times I’m acutely aware of its limitations. Interestingly, many of those limitations are not inherent to the system but programmed by the manufacturer for my supposed safety. For example, the wheelchair will only operate at a very slow speed while standing, so I can’t roll along next to someone who is walking without them having to slow down. I can’t spin around on the dance floor quickly unless I go back to a fully seated and lowered position. It’s both liberating and frustrating at the same time.

Unfortunately, many companies that develop products for people with disabilities do not presume competence. They treat us as if we are not capable of making smart decisions about our mobility devices, and design for the lowest common denominator. They put safety over freedom, which may seem wise but can put unreasonable restrictions on our bodily autonomy. Non-disabled people have the right to take risks with their bodies — why don’t we? I shouldn’t be limited from spinning on the dance floor or “walking” beside a friend indoors just because going down a steep ramp while standing would be dangerous. People with disabilities should be taught how to use technology safely, just like people without disabilities are taught to use their bodies safely.

New Future, Same Challenges

I imagine the future of cybernetics as a spectrum, ranging from people who use technology for physical and cosmetic enhancements, to those who have replacement or repaired body parts, to those whose bodies are entirely mapped to a piece of technology and their “Surrogate”-style robot walks through the world as they remain in bed. Such mapping would also surely translate to the digital world, where virtual reality bodies defy all physical limitations. As an avid user of the virtual reality platform Second Life, I’ve experienced a taste of this and can attest that friendships formed through digital bodies continue into the real world. I see all of this as opening more opportunities for people with disabilities, especially those who are currently homebound due to severe muscle weakness, chronic fatigue, and/or complete paralysis.

Unfortunately, the greatest barrier to adoption of whatever new technologies come along is already readily apparent — money, and the broken American health care system. Currently, amputees struggle to get funding for more than the most basic prostheses, and people who need power wheelchairs and other advanced mobility technology are often denied insurance coverage. Many promising products never make it to market or fail because insurance doesn’t cover them. Remember the iBot? It went under after almost no one could get funding to buy one, and although Toyota has now acquired the technology, they only seem interested in using it for marketing purposes. My guess is they discovered how grueling the FDA’s medical device approval process is and that no insurance would pay, and decided to stick to cars.

I have three forms of health insurance, but it still took a year of fighting and extra funding from the state Vocational Rehabilitation program to get my standing wheelchair. And what about when things go wrong? A crucial part of my wheelchair just broke for the second time in less than a year, and of course, insurance doesn’t want to cover the cost. As technology becomes more integrated with our bodies, its failure will increasingly mean the loss of someone’s mobility and possibly even their life.

We don’t need machines to love us. We need them to empower us to live freely in the world so we can love and be loved by other human beings. We need a health care system that recognizes the value of technology and gives us the funding and support we need to thrive. That’s a future I hope to see.

 

via Robots and the Future of Disability and Accessible Technology | The Mighty

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[WEB PAGE] Robotics in social care

Robots and autonomous systems, together with artificial intelligence, connected data and digital infrastructure could have the potential to revolutionise the way in which social and medical care for the elderly is delivered.

The rising costs of care and the need to provide much better levels of support for a growing ageing population, not only in the UK, but around the world, means that the development of these types of technology should be developed as a matter of priority by governments and health providers.

The problem is not so much that we are living longer but we are doing so with debilitating illnesses that not only undermine our health but also our mental capabilities. So, how do we help the elderly to live more fulfilling lives and not simply look to better manage physical or mental decline as we age?

In the UK, there are currently almost 12million people who are aged 65 or over. By 2045 that is expected to have reached a total of 19million and with that increase the number of people coping with illnesses, such as arthritis, heart disease of dementia is also expected to increase.

Total public spending on social care in the UK is driven by population need, the resources that are available and national priorities and in the summer of last year, the UK Government announced a significant increase in the funding that would be made available.

However, that funding was for the National Health Service (NHS) as a whole, and the announcement was criticised for failing to address problems around social care provision, especially for the elderly.

The Chief Executive of the NHS Confederation Niall Dickson said: “Social care remains the Achilles’ heel, it has been consistently underfunded, neglected and unloved by politicians over many years and the extra funding announced is clearly inadequate.”

In fact, it’s been estimated that over 1.2million older people in the UK are having to live with some level of unmet care need.

So how can technology be deployed to address this?

Robotic support for social care

According to a UK-RAS Network paper, published in 2017, ‘A Connected Care Ecosystem for Independent Living’, robotics could be used to support social care and connect users at home, in residential care and in hospital. Better care and support for independent living is certainly cheaper to manage and, more importantly, provides better support for independent living. By providing a more joined-up service it should be possible to make the transition from hospital to the home a lot easier to manage and in doing so free up resources in the NHS.

With more elderly and rising numbers of healthcare challenges technology, in the form of more portable and easier-to-use devices, could help to blur the distinctions seen between social and health care as more assistive robotic medical devices are deployed to monitor conditions in the home.

Researchers at Imperial College London have developed a robotic rehabilitation tool for stroke sufferers, for example, which helps them to improve their hand function.

Rehabilitation, such as for stroke sufferers, can often require long term supervision and support, robots and virtual reality are seen as enabling the healthcare system to provide much improved long-term support, especially if that support has been customised to meet the needs of the individual patient.

Japan is one of a growing number of developed countries that is having to confront the problem of an ageing population – and with over 25 per cent of the population over 65 Japan is being forced to adapt and use technology to address a rapidly ‘greying’ market.

“Japan is a super ageing society and many older people don’t know how to take care of their health,” said Kohjiro Ueki, director of the Diabetes Research Center at the National Center for Global Health and Medicine in Tokyo.

Speaking to Forbes magazine, Ueki talked about the impact of diabetes on the country’s ageing population, with over 10million people now suspected of having the disease.

The ‘Prevention of Worsening Diabetes Through Behavioural Changes’ trial uses an IoT self-monitoring system

Costs associated with the disease are soaring, but it can be easily managed. In response, Ueki and his colleagues have developed an app, which is being deployed in a controlled trial called the ‘Prevention of Worsening Diabetes Through Behavioural Changes’ which uses a IoT self-monitoring system to monitor eating habits.

The app records step counts, monitors physical activity, diet, body weight and blood performance. That data is collected and then uploaded to the Cloud and monitored by the individual’s doctor.

The trial involves over 2000 people and is one year into a two-year trial period.

The IoT has enabled doctors to better manage their patients and more sophisticated algorithms are planned that could see users receiving messages to boost their exercise levels or seek help.

Trialling technology

This is just one of many trials involving technology that is intended to help the elderly cope with long term illness or to improve their quality of life.

For example, smart tags, inserted into clothes or shoes, are being used to monitor the movements of dementia sufferers.

Successful ageing is defined as including a low probability of disease and disease-related disability, a high level of physical and cognitive functioning and an active engagement in life.

Robots could be used to assist people as they age helping them to maintain both physical and social activity, ensuring that they eat and drink appropriately and could help to promote a feeling of control and empowerment, that people tend to feel they lose as they grow older.

There are already a growing number of robotic devices that can help in the home, and robotic and autonomous systems are expected to be incorporated into everyday devices enabling independent living.

Future homes are likely to integrate technology into consumer devices expanding their functionality and ease of use. Items of furniture with embedded intelligence are now appearing. Tables, for example, are being developed to act like robots – coming to the user.

One project – iDress – is intended to develop a proactive system capable of assisting someone trying to dress, while exoskeletons are being developed to help elderly people with walking difficulties, increasing their independence and motor function. In time they could be used to replace wheelchairs.

Elderly people who are socially isolated are at much greater risk of developing a variety of ailments and while robots are good at improving an elderly person’s movement they can also play a role in keeping elderly people engaged both socially and mentally.

Loneliness and social isolation are known to have a serious impact on the health of the elderly and there are worries that as the population ages, so the problems associated with social isolation will only increase.

Japan, as we have seen, is facing a ‘greying’ crisis, and as a result has invested heavily in developing social care robots that are able to serve, communicate with and provide emotional support.

In Germany the Fraunhofer IPA has developed a Care-o-bot that has been deployed in a number of assisted living facilities and are able to carry food and drink to residents, while at the same time providing entertainment in the form of memory games.

Importantly, the robot has been programmed to keep its distance from residents, use limited gestures and reflect emotions and show that it understands and demonstrates what it intends to do.

CT Asia Robotics has developed a personal assistant that can help the user to remember to take pills and tracks their health. It can take calls from family and doctors too.

These devices are all suitable for use in a communal environment but robots designed for use in the home will need to be able to do far more.

One example is the ElliQ, which is an interactive robot that comes with an integrated tablet – not only does it track pill usage, monitor and take phone calls and the like, but it can act as a companion. It does this by providing updates on the weather or by suggesting outdoor activities and uses machine learning to better understand a user’s preferences.

Doubts?

But while the demand for robotic solutions is growing there are doubts tabout this so-called robotic revolution. Many medical professionals argue that the use of robots only compounds the problems of isolation and that people will need people in order to ensure their emotional and psychosocial well-being. Whatever the concerns, however, research does point to the fact that the use of social robots really can address issues of care and isolation and while there are some who are concerned by the deployment of robots to address these problems, the majority of robotic researchers tend to be in favour of their use.

Robot companions, which use artificial intelligence, are increasingly being used and these devices are able to interact with people on their own.

Examples include pet-like companions such as Aibo and Paro and MiRo, the latter is manufactured in the UK by Consequential Robotics, which is a spin out from the University of Sheffield.

MiRo is manufactured in the UK by Consequential Robotics

MiRo is a fully programmable autonomous robot with six senses, eight degrees of freedom and an innovative brain-inspired operating system and was developed to provide a platform suited for developing companion robots.

According to the company, MiRo is based on a simple premise, which is that animals have the social qualities that are desirable in social robots in that they are robust, good at communicating and adaptable.

Using that approach the robot is suited to robot-human interaction.

Although they can offer limited interaction these ‘pets’ have been shown to reduce feelings of loneliness and in one test case, involving the use of robotics dogs in a UK care home, brought increased levels of happiness and comfort.

When it comes to controlling robots the growing use of voice commands is proving a benefit, as many elderly people find using a touchscreen difficult.

Portsmouth University is developing speech and tablet interfaces for assistive robots that can operate inside and outside the home and is part of a much wider project being funded by the European Union, Robot-Era.

For people with conditions that affect their ability to speak clearly a team at the University of Sheffield is developing Automatic Speech Recognition technologies.

The research being undertaken into social robots is only just the beginning, but while humans are still better at providing the care and social contact needed by the elderly, robots will certainly be able to fill many gaps as the technology evolves and develops.

Should robots replace social and care workers? That’s a loaded question and most professionals would argue that there needs to be far more effort to address the wider public’s anxieties around the use of robots.

Building safety and trust in their deployment will be crucial if they are to be accepted into people’s homes. That safety needs to encompass mechanical safety, software safety and physical safety when robots have to interact with the wider world.

While there’s a long way to go, the opportunity to use robots and autonomous systems in social care
in the coming decades are profound and they are likely to have a significant role to play in enabling the elderlyto grow old actively and to do so with dignity.

Author
Neil Tyler

via Robotics in social care

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