Posts Tagged wearable

[Abstract + References] A New Approach to Design Glove-Like Wearable Hand Exoskeletons for Rehabilitation – Conference paper

Abstract

The synthesis of hand exoskeletons for rehabilitation is a challenging theoretical and technical task. A huge number of solutions have been proposed in the literature. Most of them are based on the concept to consider the phalanges of the finger as fixed to some links of the exoskeleton mechanism. This approach makes the exoskeleton synthesis a difficult problem that compels the designer to devise approximate technical solutions which, frequently, reduce the efficiency of the rehabilitation system and are rather bulky.

This paper proposes a different approach. Namely, the phalanges are not fixed to some links of the exoskeleton, but they can have a relative motion, with one or two degrees of freedom when planar systems are considered. An example is presented to show the potentiality of this approach, which makes it possible: (i) to design glove-like exoskeletons that only approximate the human finger motion; (ii) to leave the fingers have their natural motion; (iii) to adapt a wider range of patient hand sizes to a given hand exoskeleton.

References

  1. 1.
    Agarwal, P., Hechanova, A., Deshpande, A.D.: Kinematics and Dynamics of a biologically inspired index finger exoskeleton. In: Proceedings of the ASME 2013 Dynamic Systems and Control Conference DSCC 2013, Palo Alto, CA, USA, pp. 1–10 (2013)Google Scholar
  2. 2.
    Heo, P., Min, GuG, Lee, S.J., Rhee, K., Kim, J.: Current hand exoskeleton technologies for rehabilitation and assistive engineering. Int. J. Precis. Eng. Manuf. 3(5), 807–824 (2012)CrossRefGoogle Scholar
  3. 3.
    Balasubramanian, S., Klein, J., Burdet, E.: Robot-assisted rehabilitation and hand function. Curr. Opin. Neurol. 23, 661–670 (2010)CrossRefGoogle Scholar
  4. 4.
    Troncossi, M., Mozaffari-Foumashi, M., Parenti-Castelli, V.: An original classification of rehabilitation hand exoskeletons. J. Robot. Mech. Eng. Res. 1(4), 17–29 (2016)CrossRefGoogle Scholar
  5. 5.
    Abdallah, I.B., Bouteraa, Y., Rekik, C.: Design and development of 3D printed myoelectric robotic exoskeleton for hand rehabilitation. Int. J. Smart Sens. Intell. Syst. 10(2), 341–366 (2017)Google Scholar
  6. 6.
    Foumashi, M., Troncossi, M., Parenti-Castelli, V.: Design of a new hand exo-skeleton for rehabilitation of post-stroke patients. In: Romansy 19-Robot Design, Dynamics and Control, pp. 159–169 (2013)CrossRefGoogle Scholar
  7. 7.
    Yap, H.K., Hoon, J., Nashrallah, F., Goh, J.C.H., Yeow, R.C.H.: A soft exoskeleton for hand assistive and rehabilitation application using pneumatic actuators with variable stiffness. In: 2015 IEEE International Conference on Robotics and Automation, ICRA, Seattle, Washington, USA, pp. 4967–4972 (2015)Google Scholar
  8. 8.
    Arata, J., Ohmoto, K., Gassert, R., Lambercy, O., Fujimoto, H., Wada, I.: A new hand exoskeleton device for rehabilitation using a three-layered sliding spring mechanism. In: 2013 IEEE International Conference on Robotics and Automation, ICRA, Karlsruhe, Germany, pp. 3902–3907 (2013)Google Scholar
  9. 9.
    Leonardis, D., Barsotti, M., Loconsole, C., Solazzi, M., Troncossi, M., Mazzotti, M., Parenti, C.V., Procopio, C., Lamola, G., Chisari, C., Bergamasco, M., Frisoli, A.: An EMG-controlled robotic hand exoskeleton for bilateral rehabilitation. J. Haptics 8(2), 140–151 (2015)CrossRefGoogle Scholar
  10. 10.
    Gulke, J., Watcher, N.J., Geyer, T., Scholl, H., Apic, G., Mentzler, M., et al.: Motion coordination pattern during cylinder grip analyzed with a sensor glove. J. Hand Surg. 35(5), 797 (2010)CrossRefGoogle Scholar
  11. 11.
    Li, J., Wang, S., Zheng, R., Zhang, Y., Chen, Z.: Development of a hand exoskeleton system for index finger rehabilitation. Chin. J. Mech. Eng. 25(2), 223–233 (2012)CrossRefGoogle Scholar

via A New Approach to Design Glove-Like Wearable Hand Exoskeletons for Rehabilitation | SpringerLink

Advertisements

, , , , , , , , ,

Leave a comment

[BLOG POST] AlterEgo: A New Wearable Device Responds To Your Thoughts – Video

A man seen wearing the wearable alterego on this face.

Ever said “you read my mind!” to someone who said the same thing you were just about to say? Researchers at MIT are making this a reality. A new wearable invented at MIT, called AlterEgo, is a device that sits on your ear, loops behind it, and attaches to your face. What’s special about this device is that it recognizes non-verbal prompts – things that you are thinking in your mind, and responds to them. This wearable device also attaches to a computer system that translates your thoughts into a command that is understood by it, thus prompting a response.

There are certain locations on your face that generate neuromuscular signals when you think about something. Researchers working on AlterEgo worked on identifying those locations – first they found that 7 different location were consistently able to distinguish internal verbalization, and with more experiments, they started finding comparable results with just four locations, which meant that the wearable wasn’t going all over your face with electrodes and being intrusive. After identifying those signals, they sent them to a computer that could translate and analyze them, and eventually associating them with different words. The wearable responds, either in the form of an action, or in the form of an audible answer. For example, you may be looking at your Netflix screen on your TV and wanting to browse through all of the movies displayed. Just thinking “right” would make the Netflix screen to navigate to the next displayed movie. Similarly, just saying “what is the time?” to yourself in your mind will make the wearable say the time out loud to you. What’s also interesting is that the wearable uses bone conducting headphones which means that your ear is still available to you for any other conversation you may be having with another person. The researchers also tried it with a game of Chess (the user would just think about the opponent’s move and the wearable would respond by suggesting the next move), and with basic arithmetic operations.

Currently, AlterEgo has the accuracy of 92%, and responds to around 20 words. The researchers are confident that this wearable would learn more words with more training data, and would scale up very soon in the near future.

Of course, this wearable can be used by any non-verbal person, and someone who cannot operate a device (and control the device with just their thought), but other applications of this device could be communicating with others in extremely loud environments (air traffic personnel  directing flights on the tarmac or at a concert) where there would be no need to speak – just your thoughts would be communicated to the other person!

Watch the video below to learn more about the current prototype and go to the source links to learn more about AlterEgo.

Source: The Verge, MIT News

 

via AlterEgo: A New Wearable Device Responds To Your Thoughts – Assistive Technology Blog

, , , , ,

Leave a comment

[VIDEO] This wearable brain scanner could transform our understanding of how neurons ‘talk’

By Michael Price Mar. 21, 2018 
Mapping the chattering of neurons is a tricky undertaking. Arguably the best tool for eavesdropping in real time—by detecting the weak magnetic fields emitted by communicating neurons—comes with a huge caveat: Participants must keep their heads absolutely still inside an enormous scanner. That makes the method, magnetoencephalography (MEG), a no-go for young children, and it nixes studying brain behavior while people are moving. Now, scientists have developed the first device to solve those problems, a masklike instrument that can transmit brain signals even when the wearer is moving.

Despite some limits on how much of the brain’s activity can be mapped at once, neuroscientists are excited. “This is remarkable,” says MEG researcher Matti Hamalainen of Massachusetts General Hospital in Boston, who wasn’t involved in the study. “MEG is moving forward conceptually into a new era.”

When neurons interact with one another, their weak electrical current generates a tiny magnetic field. To measure it with conventional MEG, scientists have people stick their heads inside a scanner like an “old-style hair dryer at a salon,” explains physicist Richard Bowtell of the University of Nottingham in the United Kingdom. Inside the scanner are superconductors, loops of ultrasensitive magnetic sensors that need to be kept extremely cold by liquid helium.

It’s an incredibly powerful technology, Bowtell says, but a person moving just 5 millimeters will ruin any attempt to read their brain activity. To study the brain during motion-related tasks, MEG researchers have devised ingenious ways to simulate movement in virtual reality.

To work around such workarounds, Bowtell’s team created a wearable 3D-printed mask that, instead of using superconductors as sensors, relies on 13 small glass cubes filled with vaporized rubidium. These optically pumped magnetometers (OPMs) get to work when a laser pulses through the vapor, lining up the atoms in its path. When neural current from the brain generates a small magnetic field, it knocks the atoms out of formation. A sensor on the other side measures fluctuations in the light from the laser to paint a map of brain activity.

Elena Boto, a physicist at the University of Nottingham, was the first to try the mask out. To compare it to a conventional scanner, she performed a series of tasks—including bending and pointing her finger, drinking from a cup, and bouncing a ball on a paddle—while using both devices. Even though her head bobbed to and fro in the mask, the brain activity recorded was practically identical to that of the fixed scanner, the researchers report today in Nature.

Some challenges remain. To counteract interference from Earth’s magnetic field, researchers had to set up two large panels with magnetic coils on either side of the mask, limiting Boto’s range of motion. Expanding the range of motion to allow for something like walking is a technically difficult chore.

But the biggest hurdle is cost. The OPM sensors, designed and manufactured by QuSpin of Louisville, Colorado, are expensive, each costing about $7000. The 13 sensors in the current mask could target only one region of the brain at a time—many dozens more would be needed to give scientists full-brain coverage. The cost of doing that, nearly $1 million, would be prohibitively expensive for many researchers, Bowtell says, though he expects the price to drop as the technology matures.

But Timothy Roberts, a neuroradiologist who works with children with autism at the Children’s Hospital of Philadelphia in Pennsylvania, says MEG masks like this one would be worth it. Neuroscientists could one day use them to track early brain development or to record brain signals in adults with movement disorders like Parkinson’s disease. Or, says Roberts, to finally get a good look at the brain activity of his often fidgety patients. “Asking a child with autism to sit still is not very easy. Asking a toddler to sit still is impossible. … I think this work is transformative.”

via This wearable brain scanner could transform our understanding of how neurons ‘talk’ | Science | AAAS

, , , , , , ,

Leave a comment

[Abstract] Efficacy of Short-Term Robot-Assisted Rehabilitation in Patients With Hand Paralysis After Stroke: A Randomized Clinical Trial

Background: We evaluated the effectiveness of robot-assisted motion and activity in additional to physiotherapy (PT) and occupational therapy (OT) on stroke patients with hand paralysis.

Methods:A randomized controlled trial was conducted. Thirty-two patients, 34.4% female (mean ± SD age: 68.9 ± 11.6 years), with hand paralysis after stroke participated. The experimental group received 30 minutes of passive mobilization of the hand through the robotic device Gloreha (Brescia, Italy), and the control group received an additional 30 minutes of PT and OT for 3 consecutive weeks (3 d/wk) in addition to traditional rehabilitation. Outcomes included the National Institutes of Health Stroke Scale (NIHSS), Modified Ashworth Scale, Barthel Index (BI), Motricity Index (MI), short version of the Disabilities of the Arm, Shoulder and Hand (QuickDASH), and the visual analog scale (VAS) measurements. All measures were collected at baseline and end of the intervention (3 weeks).

Results: A significant effect of time interaction existed for NIHSS, BI, MI, and QuickDASH, after stroke immediately after the interventions (all, P < .001). The experimental group had a greater reduction in pain compared with the control group at the end of the intervention, a reduction of 11.3 mm compared with 3.7 mm, using the 100-mm VAS scale.

Conclusions: In the treatment of pain and spasticity in hand paralysis after stroke, robot-assisted mobilization performed in conjunction with traditional PT and OT is as effective as traditional rehabilitation.

via Efficacy of Short-Term Robot-Assisted Rehabilitation in Patients With Hand Paralysis After Stroke: A Randomized Clinical Trial – Jorge H. Villafañe, Giovanni Taveggia, Silvia Galeri, Luciano Bissolotti, Chiara Mullè, Grace Imperio, Kristin Valdes, Alberto Borboni, Stefano Negrini, 2018

, , , , , , , , , , ,

Leave a comment

[ARTICLE] Pilot testing of the spring operated wearable enhancer for arm rehabilitation (SpringWear) – Full Text

Abstract

Background

Robotic devices for neurorehabilitation of movement impairments in persons with stroke have been studied extensively. However, the vast majority of these devices only allow practice of stereotyped components of simulated functional tasks in the clinic. Previously we developed SpringWear, a wearable, spring operated, upper extremity exoskeleton capable of assisting movements during real-life functional activities, potentially in the home. SpringWear assists shoulder flexion, elbow extension and forearm supination/pronation. The assistance profiles were designed to approximate the torque required to move the joint passively through its range. These three assisted DOF are combined with two passive shoulder DOF, allowing complex multi-joint movement patterns.

Methods

We performed a cross-sectional study to assess changes in movement patterns when assisted by SpringWear. Thirteen persons with chronic stroke performed range of motion (ROM) and functional tasks, including pick and place tasks with various objects. Sensors on the device measured rotation at all 5 DOF and a kinematic model calculated position of the wrist relative to the shoulder. Within subject t-tests were used to determine changes with assistance from SpringWear.

Results

Maximum shoulder flexion, elbow extension and forearm pronation/supination angles increased significantly during both ROM and functional tasks (p < 0.002). Elbow flexion/extension ROM also increased significantly (p < 0.001). When the subjects volitionally held up the arm against gravity, extension at the index finger proximal interphalangeal joint increased significantly (p = 0.033) when assisted by SpringWear. The forward reach workspace increased 19% (p = 0.002). Nine subjects could not complete the functional tasks unassisted and only one showed improvement on task completion with SpringWear.

Conclusions

SpringWear increased the usable workspace during reaching movements, but there was no consistent improvement in the ability to complete functional tasks. Assistance levels at the shoulder were increased only until the shoulder could be voluntarily held at 90 degrees of flexion. A higher level of assistance may have yielded better results. Also combining SpringWear with HandSOME, an exoskeleton for assisting hand opening, may yield the most dramatic improvements in functional task performance. These low-cost devices can potentially reduce effort and improve performance during task practice, increasing adherence to home training programs for rehabilitation.

Background

There are 800,000 new strokes in the United States each year [1]. Many survivors experience debilitating motor impairments in the upper extremity that negatively affect functional capacity and quality of life. Impairments can include weakness [2] and lack of coordination between different muscle groups [3]. Fifty percent of stroke survivors older than 64 have persistent hemiparesis at six months post-stroke and 26% are dependent in activities of daily living (ADL) [1]. Unfortunately, a very high level of upper extremity motor control may be needed before the impaired limb is actually incorporated into ADL. Stroke patients often appear to have adequate movement ability when observed in the laboratory, but don’t use the limb with the expected regularity [4].

Neurorehabilitation of these impairments is possible with task-specific repetitive movement practice that incorporates high repetition, volitional effort, and successful completion of tasks to prevent frustration and maintain motivation [5]. Robotics has been studied extensively as a means of assisting movements with forces applied to the limb, allowing completion of movements that would otherwise be impossible to complete unassisted. A recent meta-analysis of 34 studies including 1160 subjects found that robotic devices produced larger gains in arm function, strength and ADL ability than comparison interventions [6]. However, authors concluded the advantages of robotic therapy may not be clinically relevant. The vast majority of these studies involved patients traveling to the clinic on a regimented schedule to practice components of tasks. Home-based approaches may be more effective in increasing the amount of limb use, in particular devices that can assist movements while subjects perform real-world ADL.

Many robotic treatments involve providing partial support of the arm against gravity to enable practice of reaching within a larger workspace [78]. This approach is motivated by research that has shown that many stroke patients have an abnormal synergy whereby elevation of the shoulder against gravity impairs the ability to extend the elbow [91011]. More recently, work has shown an abnormal coupling of proximal and distal arm muscles, such that activation level of proximal muscles and level of arm support can affect control of hand and wrist muscles [1213]. However current robotic approaches that provide gravity compensation do not allow practice of tasks in real-world environments, such as in the home, while standing or when performing bimanual tasks. Also, the provision of gravity support may not completely overcome distal weakness in elbow extension and forearm supination [14]. Additionally, many robotic paradigms rely on repetitive performance of components of functional tasks, for example, planar reaching movements. This contradicts motor learning studies that suggest retention and generalization of skills requires task variability [151617].

In previous work we developed a wearable passively actuated hand exoskeleton (HandSOME) that increases finger ROM and function [1819]. However, some subjects were found to be inappropriate for HandSOME because of proximal weakness, and while the HandSOME enabled adequate range of motion at the fingers, some subjects had difficulty supinating the forearm enough to properly grasp certain objects. Furthermore, finger extension ability would degrade as the arm was lifted against gravity. This motivated the development of a wearable arm exoskeleton called the spring-operated wearable enhancer (SpringWear). Springs apply an angle-dependent torque to the joints, with the goal of increasing ROM, repertoire of possible movements, task variability and success in completing tasks.

Overall, the goal was to enable effective use of the impaired limb in the home environment, thereby allowing patients a highly variable, but meaningful task practice. SpringWear can also reduce effort in task completion promoting greater adherence to home practice schedules. At the shoulder, SpringWear provides partial gravity compensation, which reduces the muscle forces at the shoulder needed to lift the arm. With proper selection of assistance level, the initiation and control of movements are still under patient control but less effort is needed and a larger ROM can be achieved. At the elbow, patients often can flex the joint, but have limited extension, so extension torques are applied to increase elbow extension range. A similar strategy is used to assist forearm supination/pronation. In order to benefit from SpringWear, patients should have some active movement at the joints, but for profoundly weak patients, this approach will not be effective. In these patients, powered exoskeletons may be needed, since they can move the limb throughout a larger workspace than spring powered devices. However, powered devices are much more expensive and complicated to integrate into a wearable device and compact designs are often high impedance, requiring sensors to infer the patient’s intended movement trajectory, which may be difficult in very low level patients.

In this study, chronic stroke patients performed a number of tasks with and without assistance from the SpringWear, and the kinematics of the movements were compared. If successful, SpringWear combined with HandSOME, may provide an inexpensive home-based intervention for a wide range of severe to moderately impaired stroke patients.

Methods

SpringWear design

An upper limb exoskeleton, in general, needs to be adaptable to different segment lengths and have a high number of DOFs in order to allow realistic movement practice with many anatomical joint axes involved [20]. With five DOFs, SpringWear was designed to provide assistance to forearm supination/pronation, elbow extension, shoulder flexion, while providing passive joints for shoulder horizontal abduction/adduction and internal/external rotation to allow realistic upper limb movements (Fig. 1). The design uses rubber bands or bungee cords as springs to provide the assistance. These profiles can be customized for each subject by adjusting the stiffness of the springs, which is dependent on impairment level.

 

Fig. 1 Full Assembly of SpringWear with back splint. Double-headed arrows represents five degrees of freedom. Assistance was applied at shoulder FE, elbow FE, and supination/pronation

[…]

Continue —> Pilot testing of the spring operated wearable enhancer for arm rehabilitation (SpringWear) | Journal of NeuroEngineering and Rehabilitation | Full Text

, , , , , , , , ,

Leave a comment

[ARTICLE] Wearable robotic exoskeleton for overground gait training in sub-acute and chronic hemiparetic stroke patients: preliminary results – Full Text PDF

BACKGROUND: Recovery of therapeutic or functional ambulatory capacity in post-stroke patients is a primary goal of rehabilitation. Wearable powered exoskeletons allow patients with gait dysfunctions to perform over-ground gait training, even immediately after the acute event.
AIM: To investigate the feasibility and the clinical effects of an over-ground walking training with a wearable powered exoskeleton in sub-acute and chronic stroke patients.
DESIGN: Prospective, pilot pre-post, open label, non-randomized experimental study.
SETTING: A single neurological rehabilitation center for inpatients and outpatients.
POPULATION: Twenty-three post-stroke patients were enrolled: 12 sub-acute (mean age: 43.8±13.3 years, 5 male and 7 female, 7 right hemiparesis and 5 left hemiparesis) and 11 chronic (mean age: 55.5±15.9 years, 7 male and 4 female, 4 right hemiparesis and 7 left hemiparesis) patients.
METHODS: Patients underwent 12 sessions (60 min/session, 3 times/week) of walking rehabilitation training using Ekso™, a wearable bionic suit that enables individuals with lower extremity disabilities and minimal forearm strength to stand up, sit down and walk over a flat hard surface with a full weight-bearing reciprocal gait. Clinical evaluations were performed at the beginning of the training period (t0), after 6 sessions (t1) and after 12 sessions (t2) and were based on the Ashworth scale, Motricity Index, Trunk Control Test, Functional Ambulation Scale, 10-Meter Walking Test, 6-Minute Walking Test, and Walking Handicap Scale. Wilcoxon’s test (P<0.05) was used to detect significant changes.
RESULTS: Statistically significant improvements were observed at the three assessment periods for both groups in Motricity Index, Functional Ambulation Scale, 10-meter walking test, and 6-minute walking test. Sub-acute patients achieved statistically significant improvement in Trunk Control Test and Walking Handicap Scale at t0-t2. Sub-acute and chronic patient did not achieve significant improvement in Ashworth scale at t0-t2.
CONCLUSIONS: Twelve sessions of over-ground gait training using a powered wearable robotic exoskeleton improved ambulatory functions in sub-acute and chronic post-stroke patients. Large, randomized multicenter studies are needed to confirm these preliminary data.
CLINICAL REHABILITATION IMPACT: To plan a completely new individual tailored robotic rehabilitation strategy after stroke, including task-oriented over-ground gait training.

Full Text PDF

via Wearable robotic exoskeleton for overground gait training in sub-acute and chronic hemiparetic stroke patients: preliminary results – European Journal of Physical and Rehabilitation Medicine 2017 October;53(5):676-84 – Minerva Medica – Journals

, , , , , ,

Leave a comment

[WEB SITE] Wearable Robot Provides Artificial Muscle Power – Rehab Managment

(a) Overview of wearing set-up of the assist wear. (b) Structure of the multilayered PVC gel actuator with two types of anode mesh electrodes. The red layer with small holes is comprised of slide electrodes to minimize the friction with the slide shafts. (c) Contraction and expansion movement of the stretching type actuator with the DC field turned on and off. (d) FlexiForce sensor-based motion detection (position estimator). (e) Power and controller. (Photo courtesy of Hashimoto laboratory)

(a) Overview of wearing set-up of the assist wear. (b) Structure of the multilayered PVC gel actuator with two types of anode mesh electrodes. The red layer with small holes is comprised of slide electrodes to minimize the friction with the slide shafts. (c) Contraction and expansion movement of the stretching type actuator with the DC field turned on and off. (d) FlexiForce sensor-based motion detection (position estimator). (e) Power and controller. (Photo courtesy of Hashimoto laboratory)

A collaborative research team from Shinshu University in Japan has designed a wearable robot to support a person’s hip joint while walking. Details of their prototype are published in Smart Materials and Structures.

“With a rapidly aging society, an increasing number of elderly people require care after suffering from stroke, and other-age related disabilities. Various technologies, devices, and robots are emerging to aid caretakers,” writes team leader Minoru Hashimoto, a professor of textile science and technology at Shinshu University, noting that several technologies meant to assist a person with walking are often cumbersome to the user.

“[In our] current study, [we] sought to develop a lightweight, soft, wearable assist wear for supporting activities of daily life for older people with weakened muscles and those with mobility issues,” he adds, in a media release from Shinshu University.

The wearable system consists of plasticized polyvinyl chloride (PVC) gel, mesh electrodes, and applied voltage. The mesh electrodes sandwich the gel, and when voltage is applied, the gel flexes and contracts, like a muscle. It’s a wearable actuator, the mechanism that causes movement.

“We thought that the electrical mechanical properties of the PVC gel could be used for robotic artificial muscles, so we started researching the PVC gel,” Hashimoto notes. “The ability to add voltage to PVC gel is especially attractive for high speed movement, and the gel moves with high speed with just a few hundred volts.”

In a preliminary evaluation, a stroke patient with some paralysis on one side of his body walked with and without the wearable system.

“We found that the assist wear enabled natural movement, increasing step length and decreasing muscular activity during straight line walking,” Hashimoto states. The researchers also found that adjusting the charge could change the level of assistance the actuator provides.

The robotic system earned first place in demonstrations with their multilayer PVC gel artificial muscle at the, “24th International Symposium on Smart Structures and Materials & Nondestructive Evaluation and Health Monitoring” for SPIE the international society for optics and photonics.

Next, the researchers plan to create a string actuator using the PVC gel, which could potentially lead to the development of fabric capable of providing more manageable external muscular support with ease, the release continues.

[Source(s): Shinshu University, Science Daily]

via Wearable Robot Provides Artificial Muscle Power – Rehab Managment

, , ,

1 Comment

[CORDIS] A sensor-fitted suit to analyse stroke patients’ movements.

The moment when stroke patients return home after treatment has always been a source of concern for both themselves and their physicians, as the latter are left blind without any feedback. But this is now a thing of the past: a novel suit fitted with 41 sensors is finally ready for commercialisation.

A sensor-fitted suit to analyse stroke patients’ movements

© Wright Studio, Shutterstock 

Could resorting to rehabilitation clinics be less of a necessity in the near future? Whilst these clinics effectively help patients to face post-stroke everyday life, stakeholders tend to agree that a better understanding of how these people function in the absence of medical support could lead to more effective rehabilitation at a lower cost.

This is what Bart Klaassen, PhD student at the University of Twente, and and a large team of researchers from across Europe have been working on under the INTERACTION project. Together they developed and validated an unobtrusive and modular system for monitoring daily life activities and for training motor function in stroke subjects, in the shape of a multi-sensor-equipped suit.

This project is presented by Klaassen and his team as a world first. ‘There has long been a great need for systems like this, but the technology simply was not ready,’ he says. ‘That is now changing rapidly, thanks to rapid developments in the fields of battery technology, wearables, smart e-textiles and big data analysis.’

The INTERACTION suit has been extensively tested on patients over a period of three months, during which they were asked to wear it under their regular clothes. The data was then transmitted, stored and processed thanks to a portable transmitter that can relay all of the information gathered through the internet to data processing servers at the University of Twente. The 41 sensors included in the suit monitor a large number of body segments, providing information on muscle strength, stretch and force.

‘We have been able to demonstrate that all the information is transmitted successfully, that this process is very efficient, and much more besides,’ Klaassen enthuses. ‘We have succeeded in modelling all of the relevant movements, and in cleaning up the data that is relevant for the therapist by filtering out the rest. Our project has delivered new techniques and methods that can be used to monitor patients at home for extended periods of time, and to identify any differences with structured clinical measurements. We are currently engaged in further research to obtain final verification that these methods are indeed an ideal way of supervising rehabilitation.’

The press release recently published by the University of Twente says no word about a potential date of commercialisation. However, the fact that both insurance companies and healthcare professionals were involved from the early stages of the project leaves little doubt that stroke patients will soon benefit from this technological breakthrough.

For more information, please see:
CORDIS project page

Source: Based on a press release from the University of Twente

 

via European Commission : CORDIS : News and Events : A sensor-fitted suit to analyse stroke patients’ movements

, , , ,

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] A novel generation of wearable supernumerary robotic fingers to compensate the missing grasping abilities in hemiparetic upper limb – Full Text PDF

Abstract

This contribution will focus on the design, analysis, fabrication, experimental characterization and evaluation of a family of prototypes of robotic extra fingers that can be used as grasp compensatory devices for hemiparetic upper limb.

The devices are the results of experimental sessions with chronic stroke patients and consultations with clinical experts. All the devices share a common principle of work which consists in opposing to the paretic hand/wrist so to restrain the motion of an object.

Robotic supernumerary fingers can be used by chronic stroke patients to compensate for grasping in several Activities of Daily Living (ADL) with a particular focus on bimanual tasks.

The devices are designed to be extremely portable and wearable. They can be wrapped as bracelets when not being used, to further reduce the encumbrance. The motion of the robotic devices can be controlled using an Electromyography (EMG) based interface embedded in a cap. The interface allows the user to control the device motion by contracting the frontalis muscle. The performance characteristics of the devices have been measured through experimental set up and the shape adaptability has been confirmed by grasping various objects with different shapes. We tested the devices through qualitative experiments based on ADL involving a group of chronic stroke patients in collaboration with by the Rehabilitation Center of the Azienda Ospedaliera Universitaria Senese.

The prototypes successfully enabled the patients to complete various bi-manual tasks. Results show that the proposed robotic devices improve the autonomy of patients in ADL and allow them to complete tasks which were previously impossible to perform.

Full Text PDF

, , , , , , , , , , ,

Leave a comment

%d bloggers like this: