Design and validation of low-cost assistive glove for hand assessment and therapy during activity of daily living-focused robotic stroke therapy

The usefulness of assistive soft robotics in the rehabilitation of patients with hand impairment: A systematic review

INTRODUCTION

Loss of hand function causes severe limitations in activity in daily living. The hand-soft robot is one of the methods that has recently been growing to increase the patient's independence. The purpose of the present systematic review was to provide a classification, a comparison, and a design overview of mechanisms and the efficacy of the soft hand robots to help researchers approach this field.

METHODS

The literature research regarding such tools was conducted in PubMed, Google Scholar, Science Direct, and Cochrane Central Register for Controlled Trials. We included peer-reviewed studies that considered a soft robot glove as an assistive device to provide function. The two investigators screened the titles and abstracts, then independently reviewed the full-text articles. Disagreements about inclusion were resolved by consensus or a third reviewer.

RESULTS

A total of 15 articles were identified, describing 210 participants (23 healthy subjects). The tools were in three categories according to their actuation type (pneumatic system, cable-driven, another design). The most critical outcomes in studies included functional tasks (fourteen studies), grip strength (four studies), range of motion (ROM) (five studies), and user satisfaction (five studies).

DISCUSSION

Function and grip parameters are the most common critical parameters for tests of hand robots. Cable-driven transmission and soft pneumatic actuators are the most common choices for the actuation unit. Radder et al. study had the highest grade from other studies. That was the only RCT among studies.

CONCLUSION

Although few soft robotic gloves can be considered ready to reach the market, it seems these tools have the potential to be practical for people with a disability. But, we lack consistent evidence of comparing two or more soft robot gloves on the hand functions. Future research needs to assess the effect of soft robotic gloves on people with hand disorders with more populations.

Electromyography and kinematics data of the hand in activities of daily living with special interest for ergonomics

This work presents a dataset of human hand kinematics and forearm muscle activation collected during the performance of a wide variety of activities of daily living (ADLs), with tagged characteristics of products and tasks. A total of 26 participants performed 161 ADLs selected to be representative of common elementary tasks, grasp types, product orientations and performance heights. 105 products were used, being varied regarding shape, dimensions, weight and type (common products and assistive devices). The data were recorded using CyberGlove instrumented gloves on both hands measuring 18 degrees of freedom on each and seven surface EMG sensors per arm recording muscle activity. Data of more than 4100 ADLs is presented in this dataset as MATLAB structures with full continuous recordings, which may be used in applications such as machine learning or to characterize healthy human hand behaviour. The dataset is accompanied with a custom data visualization application (ERGOMOVMUS) as a tool for ergonomics applications, allowing visualization and calculation of aggregated data from specific task, product and/or participants' characteristics.

Smoking Cessation System for Preemptive Smoking Detection

Smoking cessation is a significant challenge for many people addicted to cigarettes and tobacco. Mobile health-related research into smoking cessation is primarily focused on mobile phone data collection either using self-reporting or sensor monitoring techniques. In the past 5 years with the increased popularity of smartwatch devices, research has been conducted to predict smoking movements associated with smoking behaviors based on accelerometer data analyzed from the internal sensors in a user's smartwatch. Previous smoking detection methods focused on classifying current user smoking behavior. For many users who are trying to quit smoking, this form of detection may be insufficient as the user has already relapsed. In this paper, we present a smoking cessation system utilizing a smartwatch and finger sensor that is capable of detecting pre-smoking activities to discourage users from future smoking behavior. Pre-smoking activities include grabbing a pack of cigarettes or lighting a cigarette and these activities are often immediately succeeded by smoking. Therefore, through accurate detection of pre-smoking activities, we can alert the user before they have relapsed. Our smoking cessation system combines data from a smartwatch for gross accelerometer and gyroscope information and a wearable finger sensor for detailed finger bend-angle information. We compare the results of a smartwatch-only system with a combined smartwatch and finger sensor system to illustrate the accuracy of each system. The combined smartwatch and finger sensor system performed at an 80.6% accuracy for the classification of pre-smoking activities compared to 47.0% accuracy of the smartwatch-only system.

Reducing Anthropomorphic Hand Degrees of Actuation with Grasp-Function-Dependent and Joint-Element-Sparse Hand Synergies

In this paper, a set of grasp-function-dependent and joint-element-sparse hand synergies was proposed. First, hand synergies were extracted from five basic categories of movements by principal component analysis (PCA). Then, varimax rotation was applied on these synergies, so each sparse synergy only represented a limited number of joints. Next, according to the contribution to these sparse synergies, finger joints were clustered into different joint modules. Finally, integrating the joint modules in different categories of hand movements, the minimum number of actuators and joint synergic modules for anthropomorphic hands were determined. The results showed that using 5 groups of joint modules and 7–9 actuators we can achieve the best performance of grasp function and motion flexibility. Furthermore, through the reasonable design of adaptive and hyperextension functional joint modules, anthropomorphic hands can better meet the requirements of different tasks like power grasping and precision pinching. Comparing with traditional finger-based actuation strategy, the joint coupling scheme achieved better anthropomorphic performance and larger workspace. These above findings will benefit the development of mechanical structure design and control method of anthropomorphic hands.

A Pilot Study of the Psychosocial Impact of Low-Cost Assistive Technology for Sexual Functioning in People with Acquired Brain Injury

People with acquired brain injury (ABI) face limitations when performing activities of daily living, including sexuality. Despite the common use among this group of assistive technology to compensate for or neutralize the limitations deriving from their condition, there is very little literature on outcome measures in assistive technology for sexual functioning. The aim of this study was to explore the psychosocial impact of the use of low-cost assistive technology in people with ABI. The sample was made up of 18 users: 15 men and 3 women diagnosed with ABI. The PLISSIT model was used, as well as the Psychosocial Impact of Assistive Device Scale-PIADS as an assessment tool. Three types of low-cost assistive technology were developed: seat cushions, bed equipment, and back supports. All three types of AT obtained positive scores on the PIADS total scale and its three subscales: competence, adaptability, and self-esteem. Although the results of this study are positive, more research into outcome measures for products to improve sexual functioning in people with ABI is required.

Preliminary Results in Testing of a Novel Asymmetric Underactuated Robotic Hand Exoskeleton for Motor Impairment Rehabilitation

Robotic exoskeletons are a trending topic in both robotics and rehabilitation therapy. The research presented in this paper is a summary of robotic exoskeleton development and testing for a human hand, having application in motor rehabilitation treatment. The mechanical design of the robotic hand exoskeleton implements a novel asymmetric underactuated system and takes into consideration a number of advantages and disadvantages that arose in the literature in previous mechanical design, regarding hand exoskeleton design and also aspects related to the symmetric and asymmetric geometry and behavior of the biological hand. The technology used for the manufacturing and prototyping of the mechanical design is 3D printing. A comprehensive study of the exoskeleton has been done with and without the wearer’s hand in the exoskeleton, where multiple feedback sources are used to determine symmetric and asymmetric behaviors related to torque, position, trajectory, and laws of motion. Observations collected during the experimental testing proved to be valuable information in the field of augmenting the human body with robotic devices.

Hand Kinematics Characterization While Performing Activities of Daily Living Through Kinematics Reduction

Improving the understanding of hand kinematics during the performance of activities of daily living may help improve the control of hand prostheses and hand function assessment. This work identifies sparse synergies (each degree of freedom is present mainly in only one synergy), representative of the global population, with emphasis in unveiling the coordination of joints with small range of motion (palmar arching and fingers abduction). The study is the most complete study described in the literature till now, involving 22 healthy subjects and 26 representative day-to-day life activities. Principal component analysis was used to reduce the original 16 angles recorded with an instrumented glove. Five synergies explained 75% of total variance: closeness (coordinated flexion and abduction of metacarpophalangeal finger joints), digit arching (flexion of proximal interphalangeal joints), palmar-thumb coordination (coordination of palmar arching and thumb carpometacarpal flexion), thumb opposition, and thumb arch. The temporal evolution of these synergies is provided during reaching per intended grasp and during manipulation per specific task, which could be used as normative patterns for the global population. Reaching has been observed to require the modulation of closeness, digit arch and thumb opposition synergies, with different control patterns per grasp. All the synergies are very important during manipulation and need to be modulated for all the tasks. Finally, groups of tasks with similar kinematic requirements in terms of synergies have been identified, which could benefit the selection of tasks for rehabilitation and hand function assessments.

A large calibrated database of hand movements and grasps kinematics

Modelling hand kinematics is a challenging problem, crucial for several domains including robotics, 3D modelling, rehabilitation medicine and neuroscience. Currently available datasets are few and limited in the number of subjects and movements. The objective of this work is to advance the modelling of hand kinematics by releasing and validating a large publicly available kinematic dataset of hand movements and grasp kinematics. The dataset is based on the harmonization and calibration of the kinematics data of three multimodal datasets previously released (Ninapro DB1, DB2 and DB5, that include electromyography, inertial and dynamic data). The novelty of the dataset is related to the high number of subjects (77) and movements (40 movements, each repeated several times) for which we release for the first time calibrated kinematic data, resulting in the largest available kinematic dataset. Differently from the previous datasets, the data are also calibrated to avoid sensor nonlinearities. The validation confirms that the data are not affected by experimental procedures and that they are similar to data acquired in real-life conditions.

Measurement(s)	movement quality • grasps kinematics • muscle electrophysiology trait
Technology Type(s)	sensor • electromyography
Factor Type(s)	type of movement • joint movement repetition • age • sex • left-handed or right-handed • weight • height • body mass index
Sample Characteristic - Organism	Homo sapiens

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11341679

A calibrated database of kinematics and EMG of the forearm and hand during activities of daily living

Linking hand kinematics and forearm muscle activity is a challenging and crucial problem for several domains, such as prosthetics, 3D modelling or rehabilitation. To advance in this relationship between hand kinematics and muscle activity, synchronised and well-defined data are needed. However, currently available datasets are scarce, and the presented tasks and data are often limited. This paper presents the KIN-MUS UJI Dataset that contains 572 recordings with anatomical angles and forearm muscle activity of 22 subjects while performing 26 representative activities of daily living. This dataset is, to our knowledge, the biggest currently available hand kinematics and muscle activity dataset to focus on goal-oriented actions. Data were recorded using a CyberGlove instrumented glove and surface EMG electrodes, both properly synchronised. Eighteen hand anatomical angles were obtained from the glove sensors by a validated calibration procedure. Surface EMG activity was recorded from seven representative forearm areas. The statistics verified that data were not affected by the experimental procedures and were similar to the data acquired under real-life conditions.

An instrumented glove for monitoring hand function

The measurement of hand kinematics is important for the assessment and rehabilitation of the paralysed hand. The traditional method of hand function assessment uses a mechanical or electronic goniometer placed across the joint of interest to measure the range of joint movement. Mechanical goniometers are imprecise and lack the ability to provide a dynamic measurement; electronic goniometers are expensive and cumbersome to use during therapy. An alternative to the goniometric based assessment is to use inertial motion sensors to monitor the hand movement-these can be incorporated in a glove. In this paper, we present the design of an instrumented glove equipped with Magnetic, Angular Rate and Gravity (MARG) sensors for the objective evaluation of hand function. The instrumented glove presented in this paper is designed to assess the range of movement of the hand and also monitor the hand function during the course of hand rehabilitation. Static and dynamic calibrations were performed for the Euler angles calculated from the MARG sensors. The results are also presented for physiological flexion/extension of the wrist (relative roll), flexion/extension of elbow (relative pitch), and internal rotation/external rotation (relative yaw). The static calibration results gave mean absolute errors of 4.1° for roll, 4.0° for pitch, and 4.6° for yaw. From the dynamic calibration, the speed of response to a step change gave a convergence time of 0.4 s; sinusoidally oscillating movement gave good tracking at 0.2 Hz but exhibits overshoot errors at higher frequencies which were tested to be 1 Hz. We present the results of the calibration of the instrumented glove (one sensor pair measuring one joint angle) measuring anatomical joint angles-mean absolute errors during static calibration: 6.3° for a relative roll (wrist flexion/extension), 5.0° for relative pitch (elbow flexion/extension), and 4.5° for relative yaw (shoulder internal rotation/external rotation). The experimental results from the instrumented glove are promising, and it can be used as an alternative to the traditional goniometer based hand function assessments.

Design and development of a pool and billiards assistive device for the physically challenged

This research entailed the development and prototyping of a bespoke assistive device for a subject who was a local pool and billiards championship player. The subject was diagnosed with a brain tumor and had to undergo surgery followed by chemotherapy to completely remove the mass in the brain. Following this, there was some loss in motor skills on the right side of his body affecting his gait and grip on objects and his ability to play pool and billiards. Concepts were developed to enable the subject to regain some form. A final design was made, with subsequent alterations for fit and comfort. Testing was done over a 7-day period and results using aid were compared without using any aid over a similar period. There was an 88% decrease in time taken to execute the shot, a 140% increase in strength of shot and a 75% increase in accuracy. The results suggest greater improvement in these performance characteristics with extended use of the device. The device also serves to improve the quality of life of the subject. Implications for Rehabilitation A subject lost some physical ability following the removal of a brain tumor. A bespoke design was found to significantly enhance the performance of the subject in pool and billiards, a game that the subject loved to play before loss of the physical ability. Of increasing importance to those that have lost physical ability is the aim to restore quality of life similar to before the loss of the physical ability, especially with respect to activities that a subject would have been motivated to do due to intrinsic love/interest of the activity.

Across-subject calibration of an instrumented glove to measure hand movement for clinical purposes

Motion capture of all degrees of freedom of the hand collected during performance of daily living activities remains challenging. Instrumented gloves are an attractive option because of their higher ease of use. However, subject-specific calibration of gloves is lengthy and has limitations for individuals with disabilities. Here, a calibration procedure is presented, consisting in the recording of just a simple hand position so as to allow capture of the kinematics of 16 hand joints during daily life activities even in case of severe injured hands. 'across-subject gains' were obtained by averaging the gains obtained from a detailed subject-specific calibration involving 44 registrations that was repeated three times on multiple days to 6 subjects. In additional 4 subjects, joint angles that resulted from applying the 'across-subject calibration' or the subject-specific calibration were compared. Global errors associated with the 'across-subject calibration' relative to the detailed, subject-specific protocol were small (bias: 0.49°; precision: 4.45°) and comparable to those that resulted from repeating the detailed protocol with the same subject on multiple days (0.36°; 3.50°). Furthermore, in one subject, performance of the 'across-subject calibration' was directly compared to another fast calibration method, expressed relative to a videogrammetric protocol as a gold-standard, yielding better results.

A structured overview of trends and technologies used in dynamic hand orthoses

The development of dynamic hand orthoses is a fast-growing field of research and has resulted in many different devices. A large and diverse solution space is formed by the various mechatronic components which are used in these devices. They are the result of making complex design choices within the constraints imposed by the application, the environment and the patient's individual needs. Several review studies exist that cover the details of specific disciplines which play a part in the developmental cycle. However, a general collection of all endeavors around the world and a structured overview of the solution space which integrates these disciplines is missing. In this study, a total of 165 individual dynamic hand orthoses were collected and their mechatronic components were categorized into a framework with a signal, energy and mechanical domain. Its hierarchical structure allows it to reach out towards the different disciplines while connecting them with common properties. Additionally, available arguments behind design choices were collected and related to the trends in the solution space. As a result, a comprehensive overview of the used mechatronic components in dynamic hand orthoses is presented.

Changes in skeletal muscle perfusion and spasticity in patients with poststroke hemiparesis treated by robotic assistance (Gloreha) of the hand

[Purpose] The purpose of this case series was to determine the effects of robot-assisted hand rehabilitation with a Gloreha device on skeletal muscle perfusion, spasticity, and motor function in subjects with poststroke hemiparesis. [Subjects and Methods] Seven patients, 2 women and 5 men (mean ± SD age: 60.5 ±6.3 years), with hemiparesis (>6 months poststroke), received passive mobilization of the hand with a Gloreha (Idrogenet, Italy), device (30 min per day; 3 sessions a week for 3 weeks). The outcome measures were the total hemoglobin profiles and tissue oxygenation index (TOI) in the muscle tissue evaluated through near-infrared spectroscopy. The Motricity Index and modified Ashworth Scale for upper limb muscles were used to assess mobility of the upper extremity. [Results] Robotic assistance reduced spasticity after the intervention by 68.6% in the upper limb. The Motricity Index was unchanged in these patients after treatment. Regarding changes in muscle perfusion, significant improvements were found in total hemoglobin. There were significant differences between the pre- and posttreatment modified Ashworth scale. [Conclusion] The present work provides novel evidence that robotic assistance of the hand induced changes in local muscle blood flow and oxygen supply, diminished spasticity, and decreased subject-reported symptoms of heaviness and stiffness in subjects with post-stroke hemiparesis.

Design and Kinematic Evaluation of a Novel Joint-Specific Play Controller: Application for Wrist and Forearm Therapy

BACKGROUND

The wrist extensors and flexors are profoundly affected in most children with hemiparetic cerebral palsy (CP) and are the major target of physical therapists' and occupational therapists' efforts to restore useful hand functions. A limitation of any therapeutic or exercise program can be the level of the child's engagement or adherence. The proposed approach capitalizes on the primary learning avenue for children: toy play.

OBJECTIVE

This study aimed to develop and evaluate the measurement accuracy of innovative, motion-specific play controllers that are engaging rehabilitative devices for enhancing therapy and promoting neural plasticity and functional recovery in children with CP.

DESIGN

Design objectives of the play controller included a cost-effective, home-based supplement to physical therapy, the ability to calibrate the controller so that play can be accomplished with any active range of motion, and the capability of logging play activity and wrist motion over week-long periods.

METHODS

Accuracy of the play controller in measuring wrist flexion-extension was evaluated in 6 children who were developing in a typical manner, using optical motion capture of the wrist and forearm as the gold standard.

RESULTS

The error of the play controller was estimated at approximately 5 degrees in both maximum wrist flexion and extension.

LIMITATIONS

Measurements were taken during a laboratory session, with children without CP, and no toy or computer game was interfaced with the play controller. Therefore, the potential engagement of the proposed approach for therapy remains to be evaluated.

CONCLUSIONS

This study presented the concept, development, and wrist tracking accuracy of an inexpensive approach to extremity therapy that may have a health benefit for children with hemiparesis, and potentially for patients of any age with a wide range of extremity neuromotor impairments.

Evaluation of hand motion capture protocol using static computed tomography images: application to an instrumented glove

There has been a marked increase in the use of hand motion capture protocols in the past 20 yr. However, their absolute accuracies and precisions remain unclear. The purpose of this technical brief was to present a method for evaluating the accuracy and precision of the joint angles determined by a hand motion capture protocol using simultaneously collected static computed tomography (CT) images. The method consists of: (i) recording seven functional postures using both the motion capture protocol and a CT scanner; (ii) obtaining principal axes of the bones in each method; (iii) calculating the flexion angle at each joint for each method as the roll angle of the composite, sequential, roll-pitch-yaw rotations relating the orientation of the distal bone to the proximal bone; and (iv) comparing corresponding joint angle measurements. For demonstration, we applied the method to a Cyberglove protocol. Accuracy and precision of the instrumented-glove protocol were calculated as the mean and standard deviation, respectively, of the differences between the angles determined from the Cyberglove output and the CT images across the seven postures. Implementation in one subject highlighted substantial errors, especially for the distal joints of the fingers. This technical note both clearly demonstrates the need for future work and introduces a solid, technical approach with the potential to improve the current state of such assessments in our field.

Robotic therapy provides a stimulus for upper limb motor recovery after stroke that is complementary to and distinct from conventional therapy

BACKGROUND

Individuals with chronic stroke often have long-lasting upper extremity impairments that impede function during activities of daily living. Rehabilitation robotics have shown promise in improving arm function, but current systems do not allow realistic training of activities of daily living. We have incorporated the ARMin III and HandSOME device into a novel robotic therapy modality that provides functional training of reach and grasp tasks.

OBJECTIVE

To compare the effects of equal doses of robotic and conventional therapy in individuals with chronic stroke.

METHODS

Subjects were randomized to 12 hours of robotic or conventional therapy and then crossed over to the other therapy type after a 1-month washout period. Twelve moderate to severely impaired individuals with chronic stroke were enrolled, and 10 completed the study.

RESULTS

Across the 3-month study period, subjects showed significant improvements in the Fugl-Meyer (P = .013) and Box and Blocks tests (P = .028). The robotic intervention produced significantly greater improvements in the Action Research Arm Test than conventional therapy (P = .033). Gains in the Box and Blocks test from conventional therapy were larger than from robotic therapy in subjects who received conventional therapy after robotic therapy (P = .044).

CONCLUSIONS

Data suggest that robotic therapy can elicit improvements in arm function that are distinct from conventional therapy and supplements conventional methods to improve outcomes. Results from this pilot study should be confirmed in a larger study.

Remote vibrotactile noise improves light touch sensation in stroke survivors' fingertips via stochastic resonance

Background and purpose

Stroke rehabilitation does not often integrate both sensory and motor recovery. While subthreshold noise was shown to enhance sensory signal detection at the site of noise application, having a noise-generating device at the fingertip to enhance fingertip sensation and potentially enhance dexterity for stroke survivors is impractical, since the device would interfere with object manipulation. This study determined if remote application of subthreshold vibrotactile noise (away from the fingertips) improves fingertip tactile sensation with potential to enhance dexterity for stroke survivors.

Methods

Index finger and thumb pad sensation was measured for ten stroke survivors with fingertip sensory deficit using the Semmes-Weinstein Monofilament and Two-Point Discrimination Tests. Sensation scores were measured with noise applied at one of three intensities (40%, 60%, 80% of the sensory threshold) to one of four locations of the paretic upper extremity (dorsal hand proximal to the index finger knuckle, dorsal hand proximal to the thumb knuckle, dorsal wrist, volar wrist) in a random order, as well as without noise at beginning (Pre) and end (Post) of the testing session.

Results

Vibrotactile noise of all intensities and locations instantaneously and significantly improved Monofilament scores of the index fingertip and thumb tip (p < .01). No significant effect of the noise was seen for the Two-Point Discrimination Test scores.

Conclusions

Remote application of subthreshold (imperceptible) vibrotactile noise at the wrist and dorsal hand instantaneously improved stroke survivors’ light touch sensation, independent of noise location and intensity. Vibrotactile noise at the wrist and dorsal hand may have enhanced the fingertips’ light touch sensation via stochastic resonance and interneuronal connections. While long-term benefits of noise in stroke patients warrants further investigation, this result demonstrates potential that a wearable device applying vibrotactile noise at the wrist could enhance sensation and grip ability without interfering with object manipulation in everyday tasks.

ARhT: a portable hand therapy system

We introduce ARhT (Automated Relearning hand Therapy), a portable hand therapy system that enables a user to perform physical therapy at the comfort of their own home. This reduces rehabilitation time, enhances the user experience, reduces cost and provides accountability to physical therapy sessions. ARhT complements traditional therapy methods by interacting with the user in real time and providing the patient user friendly instructions, feedback, and progress tracking. The therapist pre-selects the hand gestures that comprise every workout and can view session information on a patient to patient basis within a standalone web application. ARhT incorporates a data acquisition subsystem which houses EMG sensors and a custom computation and communication board. The sensor data is transmitted to an Android smartphone that determines the user performance and interacts with the user through a graphical user interface. Our results show that our system recognizes hand therapy gestures with over 95% accuracy.

Subject-specific myoelectric pattern classification of functional hand movements for stroke survivors

In this study, we developed a robust subject-specific electromyography (EMG) pattern classification technique to discriminate intended manual tasks from muscle activation patterns of stroke survivors. These classifications will enable volitional control of assistive devices, thereby improving their functionality. Twenty subjects with chronic hemiparesis participated in the study. Subjects were instructed to perform six functional tasks while their muscle activation patterns were recorded by ten surface electrodes placed on the forearm and hand of the impaired limb. In order to identify intended functional tasks, a pattern classifier using linear discriminant analysis was applied to the EMG feature vectors. The classification accuracy was mainly affected by the impairment level of the subject. Mean classification accuracy was 71.3% for moderately impaired subjects (Chedoke Stage of Hand 4 and 5), and 37.9% for severely impaired subjects (Chedoke Stage of Hand 2 and 3). Most misclassification occurred between grip tasks of similar nature, for example, among pinch, key, and three-fingered grips, or between cylindrical and spherical grips. EMG signals from the intrinsic hand muscles significantly contributed to the inter-task variability of the feature vectors, as assessed by the inter-task squared Euclidean distance, thereby indicating the importance of intrinsic hand muscles in functional manual tasks. This study demonstrated the feasibility of the EMG pattern classification technique to discern the intent of stroke survivors. Future work should concentrate on the construction of a subject-specific EMG classification paradigm that carefully considers both functional and physiological impairment characteristics of each subject in the target task selection and electrode placement procedures.

Bilateral assessment of functional tasks for robot-assisted therapy applications

This article presents a novel evaluation system along with methods to evaluate bilateral coordination of arm function on activities of daily living tasks before and after robot-assisted therapy. An affordable bilateral assessment system (BiAS) consisting of two mini-passive measuring units modeled as three degree of freedom robots is described. The process for evaluating functional tasks using the BiAS is presented and we demonstrate its ability to measure wrist kinematic trajectories. Three metrics, phase difference, movement overlap, and task completion time, are used to evaluate the BiAS system on a bilateral symmetric (bi-drink) and a bilateral asymmetric (bi-pour) functional task. Wrist position and velocity trajectories are evaluated using these metrics to provide insight into temporal and spatial bilateral deficits after stroke. The BiAS system quantified movements of the wrists during functional tasks and detected differences in impaired and unimpaired arm movements. Case studies showed that stroke patients compared to healthy subjects move slower and are less likely to use their arm simultaneously even when the functional task requires simultaneous movement. After robot-assisted therapy, interlimb coordination spatial deficits moved toward normal coordination on functional tasks.

Advances in upper limb stroke rehabilitation: a technology push

Strokes affect thousands of people worldwide leaving sufferers with severe disabilities affecting their daily activities. In recent years, new rehabilitation techniques have emerged such as constraint-induced therapy, biofeedback therapy and robot-aided therapy. In particular, robotic techniques allow precise recording of movements and application of forces to the affected limb, making it a valuable tool for motor rehabilitation. In addition, robot-aided therapy can utilise visual cues conveyed on a computer screen to convert repetitive movement practice into an engaging task such as a game. Visual cues can also be used to control the information sent to the patient about exercise performance and to potentially address psychosomatic variables influencing therapy. This paper overviews the current state-of-the-art on upper limb robot-mediated therapy with a focal point on the technical requirements of robotic therapy devices leading to the development of upper limb rehabilitation techniques that facilitate reach-to-touch, fine motor control, whole-arm movements and promote rehabilitation beyond hospital stay. The reviewed literature suggest that while there is evidence supporting the use of this technology to reduce functional impairment, besides the technological push, the challenge ahead lies on provision of effective assessment of outcome and modalities that have a stronger impact transferring functional gains into functional independence.