Introductory analysis of human upper body after stroke

The most reliable prognostic factors associated with Upper Extremity (UE) recovery are localized motor impairments, especially in the musculature of the hand and abduction of the shoulder in the first days after a stroke. Evaluation of the biomechanics of the hand allows an accurate identification of the motion arcs of the digital joints. Objective: Assess the prognostic value of the range of motion of the finger joints using an instrumental glove (CyberGlove II®) one week after stroke for UE functional recovery at 6 months. Methodology: A prospective, longitudinal, observational study with follow-ups at 3-4 days, 1 week, 3 and 6months of patients with UE motor impairment. Variables collected included: demographic data, level of stroke severity (NIHSS), deep sensitivity, sphincter incontinence, Fugl Meyer Assessment of UE (FM-UE), muscle balance with the Medical Research Council (MRC), muscle tone (Modified Ashworth Scale) and pre- and post-stroke functional ability (Barthel Index and Modified Rankin Scale). Active range of motion of the metacarpophalangeal and interphalangeal joints of the index, middle finger, annulary, and little finger was assessed with CyberGlove II® without and against gravity. The dependent variable UE function was evaluated with the Action Research Arm Test (ARAT) categorized as good function (ARAT=10) and poor function (ARAT<10). Results: 31 patients were included, 18 of which completed the 6-month follow-up. Mean age was 68.2 years (SD = 9.1) and 72.2 % were men. A total of 77.8 % of strokes were ischemic, and 50 % of these were lacunar. Mean NIHSS score was 9.2 (SD = 5.5). Motor NIHSS of UE, FM-UE and MRC of the flexion-extension musculature of the digits and wrist were prognostic factors for the recovery of UE function.Peer ReviewedPostprint (author's final draft

Human-centered Electric Prosthetic (HELP) Hand

Through a partnership with Indian non-profit Bhagwan Mahaveer Viklang Sahayata Samiti, we designed a functional, robust, and and low cost electrically powered prosthetic hand that communicates with unilateral, transradial, urban Indian amputees through a biointerface. The device uses compliant tendon actuation, a small linear servo, and a wearable garment outfitted with flex sensors to produce a device that, once placed inside a prosthetic glove, is anthropomorphic in both look and feel. The prosthesis was developed such that future groups can design for manufacturing and distribution in India

Design and Validation of an MR Conditional Upper Extremity Evaluation System to Study Brain Activation Patterns after Stroke

Stroke is the third leading cause of death and second most frequent cause of disability in the United States. Stroke rehabilitation methods have been developed to induce the cortical reorganization and motor-relearning that leads to stroke recovery. In this thesis, we designed and developed an MR conditional upper extremity reach and grasp movement evaluation system for the stroke survivors to study their kinematic performances in reach and grasp movement and the relationship between kinematic metrics and the recovery level measured by clinical assessment methods. We also applied the system into the functional MRI experiments to identify the ability to study motor performance with the system inside the scanner and the reach, grasp and reach-to-grasp movements related brain activation patterns. Our experiments demonstrates that ours system is an MR conditional system in the 3.0 Tesla magnetic field. It is able to measure the stroke survivors\u27 reach and grasp movement in terms of grasp aperture and elbow joint angles. We used the Mann Whitney U test to examine the significant metrics in each tasks and principle component analysis to decide the major metrics that are associated with the outcome. Then we discovered better recovery scores are associated with these major kinematic metrics such as larger maximal velocity, larger mean velocity, larger maximal movement angle, and longer time to peak velocity. Additional to these metrics, time to maximal angle, time to target and time to peak velocity could also be used as additional metrics to help predict the recovery and assess robot-assisted therapy and optimize task-oriented rehabilitation strategy. We also identified the movement related brain activations in the motor and sensory areas as well as cerebellum in both normal and stroke survivors

Real-time human ambulation, activity, and physiological monitoring:taxonomy of issues, techniques, applications, challenges and limitations

Automated methods of real-time, unobtrusive, human ambulation, activity, and wellness monitoring and data analysis using various algorithmic techniques have been subjects of intense research. The general aim is to devise effective means of addressing the demands of assisted living, rehabilitation, and clinical observation and assessment through sensor-based monitoring. The research studies have resulted in a large amount of literature. This paper presents a holistic articulation of the research studies and offers comprehensive insights along four main axes: distribution of existing studies; monitoring device framework and sensor types; data collection, processing and analysis; and applications, limitations and challenges. The aim is to present a systematic and most complete study of literature in the area in order to identify research gaps and prioritize future research directions

A virtual hand assessment system for efficient outcome measures of hand rehabilitation

Previously held under moratorium from 1st December 2016 until 1st December 2021.Hand rehabilitation is an extremely complex and critical process in the medical rehabilitation field. This is mainly due to the high articulation of the hand functionality. Recent research has focused on employing new technologies, such as robotics and system control, in order to improve the precision and efficiency of the standard clinical methods used in hand rehabilitation. However, the designs of these devices were either oriented toward a particular hand injury or heavily dependent on subjective assessment techniques to evaluate the progress. These limitations reduce the efficiency of the hand rehabilitation devices by providing less effective results for restoring the lost functionalities of the dysfunctional hands. In this project, a novel technological solution and efficient hand assessment system is produced that can objectively measure the restoration outcome and, dynamically, evaluate its performance. The proposed system uses a data glove sensorial device to measure the multiple ranges of motion for the hand joints, and a Virtual Reality system to return an illustrative and safe visual assistance environment that can self-adjust with the subject’s performance. The system application implements an original finger performance measurement method for analysing the various hand functionalities. This is achieved by extracting the multiple features of the hand digits’ motions; such as speed, consistency of finger movements and stability during the hold positions. Furthermore, an advanced data glove calibration method was developed and implemented in order to accurately manipulate the virtual hand model and calculate the hand kinematic movements in compliance with the biomechanical structure of the hand. The experimental studies were performed on a controlled group of 10 healthy subjects (25 to 42 years age). The results showed intra-subject reliability between the trials (average of crosscorrelation ρ = 0.7), inter-subject repeatability across the subject’s performance (p > 0.01 for the session with real objects and with few departures in some of the virtual reality sessions). In addition, the finger performance values were found to be very efficient in detecting the multiple elements of the fingers’ performance including the load effect on the forearm. Moreover, the electromyography measurements, in the virtual reality sessions, showed high sensitivity in detecting the tremor effect (the mean power frequency difference on the right Vextensor digitorum muscle is 176 Hz). Also, the finger performance values for the virtual reality sessions have the same average distance as the real life sessions (RSQ =0.07). The system, besides offering an efficient and quantitative evaluation of hand performance, it was proven compatible with different hand rehabilitation techniques where it can outline the primarily affected parts in the hand dysfunction. It also can be easily adjusted to comply with the subject’s specifications and clinical hand assessment procedures to autonomously detect the classification task events and analyse them with high reliability. The developed system is also adaptable with different disciplines’ involvements, other than the hand rehabilitation, such as ergonomic studies, hand robot control, brain-computer interface and various fields involving hand control.Hand rehabilitation is an extremely complex and critical process in the medical rehabilitation field. This is mainly due to the high articulation of the hand functionality. Recent research has focused on employing new technologies, such as robotics and system control, in order to improve the precision and efficiency of the standard clinical methods used in hand rehabilitation. However, the designs of these devices were either oriented toward a particular hand injury or heavily dependent on subjective assessment techniques to evaluate the progress. These limitations reduce the efficiency of the hand rehabilitation devices by providing less effective results for restoring the lost functionalities of the dysfunctional hands. In this project, a novel technological solution and efficient hand assessment system is produced that can objectively measure the restoration outcome and, dynamically, evaluate its performance. The proposed system uses a data glove sensorial device to measure the multiple ranges of motion for the hand joints, and a Virtual Reality system to return an illustrative and safe visual assistance environment that can self-adjust with the subject’s performance. The system application implements an original finger performance measurement method for analysing the various hand functionalities. This is achieved by extracting the multiple features of the hand digits’ motions; such as speed, consistency of finger movements and stability during the hold positions. Furthermore, an advanced data glove calibration method was developed and implemented in order to accurately manipulate the virtual hand model and calculate the hand kinematic movements in compliance with the biomechanical structure of the hand. The experimental studies were performed on a controlled group of 10 healthy subjects (25 to 42 years age). The results showed intra-subject reliability between the trials (average of crosscorrelation ρ = 0.7), inter-subject repeatability across the subject’s performance (p > 0.01 for the session with real objects and with few departures in some of the virtual reality sessions). In addition, the finger performance values were found to be very efficient in detecting the multiple elements of the fingers’ performance including the load effect on the forearm. Moreover, the electromyography measurements, in the virtual reality sessions, showed high sensitivity in detecting the tremor effect (the mean power frequency difference on the right Vextensor digitorum muscle is 176 Hz). Also, the finger performance values for the virtual reality sessions have the same average distance as the real life sessions (RSQ =0.07). The system, besides offering an efficient and quantitative evaluation of hand performance, it was proven compatible with different hand rehabilitation techniques where it can outline the primarily affected parts in the hand dysfunction. It also can be easily adjusted to comply with the subject’s specifications and clinical hand assessment procedures to autonomously detect the classification task events and analyse them with high reliability. The developed system is also adaptable with different disciplines’ involvements, other than the hand rehabilitation, such as ergonomic studies, hand robot control, brain-computer interface and various fields involving hand control

Virtual reality based upper extremity rehabilitation following stroke: a review

In the last decade there have been major developments in the creation of interactive virtual scenarios for the rehabilitation of motor deficits following stroke. Virtual reality technology is arising as a promising tool to diagnose, monitor and induce functional recovery after lesions to the nervous system. This evidence has grown in the last few years, as effort has been made to develop virtual scenarios that are built on the knowledge of mechanisms of recovery. In this paper we review the state of the art virtual reality techniques for rehabilitation of functionality of the upper extremities following stroke. We refer to some of the main systems that have been developed within different rehabilitative approaches such as learning by imitation, reinforced feedback, haptic feedback, augmented practice and repetition, video capture virtual reality, exoskeletons, mental practice, action observation and execution, and others. The major findings of these studies show that virtual reality technologies will become a more and more essential ingredient in the treatment of stroke and other disorders of the nervous system.info:eu-repo/semantics/publishedVersio

Force sensing glove for quantification of joint torques during stretching after spinal cord injury in the rat model.

An increasing amount of healthcare resources is used for the treatment and prevention of contractures in patients with spinal cord injury (SCI), with stretch and passive movements remaining the most prominent intervention methods. The results of both clinical trials and animal studies in recent years have shown traditional stretch therapies to be ineffective at preventing contracture and joint immobility, and have encouraged further emphasis on evidence-based practices. However, these studies only analyzed one aspect of stretching, dosage, and failed to look at the characteristic of joint torque. Recent clinical trials have unearthed the fact that the joint torque application of therapeutic stretches in the clinic not only vary by therapist, but also can be well beyond the range of torques tolerated by able-bodied individuals. A glove device utilizing force sensing resistors (FSRs) was developed to gauge joint torques. Coupled with a custom National Instruments’ LabVIEW program, the device was able to accurately measure forces, and eventually torques, applied during stretching. This study sought to explain what range of torques were being applied during stretching after SCI in the rat model in the hopes of understanding how to administer safe, effective therapeutic stretches. Six adult female Sprague-Dawley rats were mildly contused at T9 using the NYU impactor device with a 12.5 g-cm weight drop. n=2 rats were stretched 2 days per week and n=2 rats were stretched once per week using an eight minute protocol, for the first 5 weeks post-injury while controls (n=2) received no stretch therapy. Briefly, the tibialis anterior (TA) and triceps surae (TS) muscle groups were stretched by two therapists bilaterally for a minute each, totaling 4 minutes of stretch per rat per day. Kinematic assessments of stretching were accompanied by force measurement data and were used to generate comparisons between therapeutic torque and end range of motion (ROM) of the ankle. The data suggests that both once and twice per week stretching regimens were not enough to inhibit locomotor recovery or elicit a noticeable change in end ROM in such a mild injury model. There were noticeable differences in torques applied during stretching by different therapists, confirming the findings of previous studies. More importantly, the data showed that immediately after injury the normal end ROM can be achieved by applying less torque. The torque necessary to reach the end ROM increases to baseline values by week 5, potentially due to a return of the stretch reflex during spinal shock. This study urges other aspects of stretching therapy to be considered and suggests a tool for therapists to quantitatively apply safe and consistent stretching therapies to patients

Review of Wearable Devices and Data Collection Considerations for Connected Health

Wearable sensor technology has gradually extended its usability into a wide range of well-known applications. Wearable sensors can typically assess and quantify the wearer’s physiology and are commonly employed for human activity detection and quantified self-assessment. Wearable sensors are increasingly utilised to monitor patient health, rapidly assist with disease diagnosis, and help predict and often improve patient outcomes. Clinicians use various self-report questionnaires and well-known tests to report patient symptoms and assess their functional ability. These assessments are time consuming and costly and depend on subjective patient recall. Moreover, measurements may not accurately demonstrate the patient’s functional ability whilst at home. Wearable sensors can be used to detect and quantify specific movements in different applications. The volume of data collected by wearable sensors during long-term assessment of ambulatory movement can become immense in tuple size. This paper discusses current techniques used to track and record various human body movements, as well as techniques used to measure activity and sleep from long-term data collected by wearable technology devices

Robotic Fingers in Reach-to-Grasp Tasks of Rehabilitation

The REHAROB robotic upper limb rehabilitation system was improved with a custom-designed and developed hand/finger therapy module. The new module extends the scope of the applicable motion therapy from passive to active reach-to-grasp activities of daily living tasks, and the range of treated anatomical joints was also extended to every proximal and distal upper limb anatomical joint. Finger exercising and object grasping are supported with a pair of two degree-of-freedom (DOF) robotic fingers. One of the robotic fingers moves the index/middle/ring fingers together, whereas the other robotic finger moves the thumb. A novel hypothesis was established, analyzed, and tested for setting the orientation of the robotic finger moving the thumb. The robotic thumb is not aligned with the patient's thumb; its orientation is optimized in the patient's hand reference system to maximize the efficiency in the opposite grasping task. While most concurrent systems utilize virtual objects for grasping tasks, the REHAROB system exercises five carefully selected reach-and-grasp type activities of daily living (ADL) with real objects. Actuating the human finger phalanges through custom development finger orthoses is described. An advanced feature of the hand/finger therapy module is the left-right hand side changeover by only alternating the orientation of the robotic fingers and exchanging the finger orthoses

Sustainable Technology and Elderly Life

The coming years will see an exponential increase in the proportion of elderly people in our society. This accelerated growth brings with it major challenges in relation to the sustainability of the system. There are different aspects where these changes will have a special incidence: health systems and their monitoring; the development of a framework in which the elderly can develop their daily lives satisfactorily; and in the design of intelligent cities adapted to the future sociodemographic profile. The discussion of the challenges faced, together with the current technological evolution, can show possible ways of meeting the challenges. There are different aspects where these changes will have a special incidence: health systems and their monitoring; the development of a framework in which the elderly can develop their daily lives satisfactorily; and in the design of intelligent cities adapted to the future sociodemographic profile. This special issue discusses various ways in which sustainable technologies can be applied to improve the lives of the elderly. Six articles on the subject are featured in this volume. From a systematic review of the literature to the development of gamification and health improvement projects. The articles present suggestive proposals for the improvement of the lives of the elderly. The volume is a resource of interest for the scientific community, since it shows different research gaps in the current state of the art. But it is also a document that can help social policy makers and people working in this domain to planning successful projects