Posts Tagged hemiplegic

[ARTICLE] Motor Impairment and Its Influence in Gait Velocity and Asymmetry in Community Ambulating Hemiplegic Individuals – Full Text



To determine the most important motor impairments that are predictors of gait velocity and spatiotemporal symmetrical ratio in patients with stroke.


Cross-sectional, descriptive analysis study.


Human performance laboratory of the University of Santo Tomas.


Individuals with chronic stroke (N=55; 34 men, 21 women) who are community dwellers.


Not applicable.

Main Outcome Measures

The gait velocity and spatiotemporal symmetrical ratio (step length; step, stance, swing, single-leg support, and double-leg support stance times) was determined using Vicon motion capture. We also calculated motor impairment of the leg and foot using Brunnstrom’s stages of motor recovery, evaluated muscle strength using the scoring system described by Collin and Wade, and assessed spasticity using by the modified Ashworth Scale.


Regression analysis showed that plantarflexor strength is a predictor of gait velocity and all temporospatial symmetry ratio. Knee flexor and extensor strength are predictors in single-leg support time and double-leg support time symmetry ratio, respectively. On the other hand, hip adductor and quadriceps spasticity are predictors of swing time and step length symmetry ratio.


Different motor impairments are predictors of stroke gait abnormality. Interventions should be focused on these motor impairments to allow for optimal gait rehabilitation results.


Stroke results in a wide array of sensorimotor impairment, including weakness of contralateral extremities, decreased sensation and balance, spasticity, loss of motor control, and the inability to walk.1,2 Gait recovery is one of the main goals of rehabilitation because gait impairment affects the quality of life and functional status of stroke patients.3,4

In general, poststroke hemiparetic gait is slow compared with healthy individuals with asymmetry in the spatiotemporal parameters such as step length, swing time (SwT), stance time (StT), single-leg support time (SLST), and double-leg support time (DLST).3,5 However, there is a wide-range heterogeneity of gait patterns among stroke patients.2 Because of the varied gait patterns, gait speed and symmetry ratios have been used to assess gait among stroke patients.5,6 However, gait speed may be unable to determine the underlying impairments and compensatory mechanism in this patient group. Improvement may not be the result of motor recovery but could be a result of a compensatory mechanism by the nonaffected leg.7 Temporospatial parameters are usually analyzed for symmetry, and step length is usually calculated for symmetry but has a less consistent pattern.8 The pattern of temporal asymmetry is characterized by a shorter StT and a longer SwT on the affected leg.9 SwT, StT, SLST, and DLST are temporal parameters used in calculating symmetry. Although the step length ratio is the most frequently used symmetry ratio in research, it has been suggested that the temporal symmetry ratio also be analyzed. With this, gait control in the phases of gait can be better understood and targeted ambulation training could be instituted for better gait recovery.3,5,10111213 Analyzing the SLST and DLST is of interest because they have different subtasks, namely supporting the upper body during the stance phase and generating enough mechanical energy for leg propulsion respectively.12 Furthermore, there is more temporal gait asymmetry compared with spatial asymmetry, as reported by Lauzière et al in their review, in which studies reported that 60% of stroke patients had temporal asymmetry whereas only 33% to 49% had step length asymmetry.12

Studies have determined the relationship of motor deficits of muscle strength, spasticity, and motor recovery with spatiotemporal symmetry ratio.3,8,10,11,141516171819 The strength of the plantarflexors and dorsiflexors has a negative correlation with SLST symmetry ratio, whereas the strength of plantarflexors and knee extensors have a negative correlation with the step length symmetry ratio.10,11 However, a limited number of muscles were assessed. Spasticity of ankle plantarflexors was positively correlated with the symmetry ratio for step length, SwT, and SLST10,11,17 Spasticity of the knee extensors and ankle invertors was positively correlated with SwT, StT, and SLST symmetry ratio, whereas the spasticity of hip adductors and extensors was positively correlated with SwT symmetry ratio.10,11,17 Spasticity measurement is commonly measured using the modified Ashworth Scale (MAS), although Lin et al used electromyography.10,11,17

The different assessment tools used to measure stroke impairment include the Chedoke-McMaster Stroke Assessment, Fugl-Meyer Assessment, and Brunnstrom stages of stroke recovery (BSSR).3,8,10,11,14151617 These methods have been used to determine the relationship of stroke impairment with spatiotemporal symmetrical ratio.11,13,14,16171819 However, only the BSSR assesses purely motor development and reorganization of the brain after stroke. The other assessment tools include sensory impairments, postural control balance, and ambulation.11,131415,17,19 The findings regarding the correlation of BSSR with spatiotemporal symmetry ratio have been inconsistent. Ӧken and Yavuzer18 showed no correlation with SLST symmetry ratio, whereas Balasubramanian et al16 reported a negative correlation with step length symmetry ratio. However, to our knowledge, no study has determined the relationship of hemiparetic severity, the strength and level of spasticity of each lower extremity muscle group with gait speed, and the different symmetry ratio of step length, StT, SwT, SLST, and DLST. The current study hypothesized that motor impairments are predictors of gait velocity and spatiotemporal symmetrical ratio, which include step length, StT, SwT, SLST, and DLST. Motor impairments include BSSR; muscle strength of the affected lower extremity (except hip abductor and adductors); and spasticity of hamstrings, quadriceps, gastrocnemius, tibialis anterior, and hip adductors using MAS.


The study was performed at the Human Performance Laboratory of the University of Santo Tomas from July to December 2018. Ethical approval was provided by the Institutional Review Board of the University of Santo Tomas Hospital and conformed to the tenets of the Helsinki Declaration. Informed consent forms were signed by all participants before entering the study protocol. The study was designed as a cross-sectional, descriptive analysis study.


The differences and the variability in the stance time between stroke patients and healthy individuals reported in a study by Ng et al20 were used to determine the sample size for the current study. A sample size of 56 was computed, with a power of 0.90 and an alpha level of 0.05.

The inclusion criteria for the participants were men or women with unilateral hemiparesis secondary to stroke aged between 30 and 75 years who were able to understand instructions and were ambulatory (either independently or with the use of a cane). Participants with a limited range of motion for the lower extremity joints (appendix 1), or any cardiopulmonary, musculoskeletal, or other neurologic conditions that prevented them from walking at least 10 meters without pain were excluded from the study.

Outcome measures

The demographic and anthropometric data recorded included sex, age, comorbidities, height in meters, weight in kilograms, and body mass index. Stroke data included the side of hemiparesis, stroke duration, and stroke classification.

The BSSR, which ranges from stage 1 to 6, was used to assess the severity of hemiparesis, indicating no voluntary movement to mild hemiparesis that allows patients to perform an isolated joint movement.21 Muscle strength of both lower extremities was assessed using the scoring system described by Collin and Wade (table 1).22 Spasticity of the lower extremity muscles was evaluated using MAS, which ranges from 0 (no increase in muscle tone) to 5 (joints are placed in rigid flexion or extension).23

Table 1. Muscle strength grading using the scoring system of Collin and Wade22

Description of Muscle MovementScore
No movement0
Palpable contraction in muscle but no movement9
Visible movement but not full range and not against gravity14
Full range of movement against gravity but no resistance19
Full range of movement against gravity but weaker than the other side25
Normal power33

Vicon motion capture systema with 8 cameras was used to determine gait velocity and spatiotemporal asymmetry. Thirty-nine retroreflected markers were attached to the standard marker positions for data acquisition (fig 1). The Vicon motions were recorded using Nexus softwareb and were directly imported to Microsoft Excelc using a frame rate of 100 frames per second.

Fig 1. Standard marker positions for data acquisition using 3-dimensional motion capture.



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[ARTICLE] Motor Function Evaluation of Hemiplegic Upper-Extremities Using Data Fusion from Wearable Inertial and Surface EMG Sensors – Full Text


Quantitative evaluation of motor function is of great demand for monitoring clinical outcome of applied interventions and further guiding the establishment of therapeutic protocol. This study proposes a novel framework for evaluating upper limb motor function based on data fusion from inertial measurement units (IMUs) and surface electromyography (EMG) sensors. With wearable sensors worn on the tested upper limbs, subjects were asked to perform eleven straightforward, specifically designed canonical upper-limb functional tasks. A series of machine learning algorithms were applied to the recorded motion data to produce evaluation indicators, which is able to reflect the level of upper-limb motor function abnormality. Sixteen healthy subjects and eighteen stroke subjects with substantial hemiparesis were recruited in the experiment. The combined IMU and EMG data yielded superior performance over the IMU data alone and the EMG data alone, in terms of decreased normal data variation rate (NDVR) and improved determination coefficient (DC) from a regression analysis between the derived indicator and routine clinical assessment score. Three common unsupervised learning algorithms achieved comparable performance with NDVR around 10% and strong DC around 0.85. By contrast, the use of a supervised algorithm was able to dramatically decrease the NDVR to 6.55%. With the proposed framework, all the produced indicators demonstrated high agreement with the routine clinical assessment scale, indicating their capability of assessing upper-limb motor functions. This study offers a feasible solution to motor function assessment in an objective and quantitative manner, especially suitable for home and community use.

1. Introduction

Motor function impairment is the sequelae of lots of neuromuscular diseases or injuries, such as strokes, spinal cord injuries, cerebral palsy and some others. It may significantly reduce self-care ability and quality of life for the patients, and therefore represent a heavy burden for their family and society [1]. A variety of therapeutic approaches have been developed for the clinical management and treatment of motor impairments, where assessment of motor function is always involved. The motor function evaluation is able not only to quantify the degree of motor dysfunction in patients but also to measure the clinical outcome of the applied intervention. It further offers important guidance for clinicians to establish rehabilitation protocols for individual patients. Therefore, the clinical evaluation of motor function is considered as a prerequisite to the development of effective approaches towards enhanced therapeutic effect [2].Generally, the use of standardized assessment scales serves as the clinical routine to measure the motor function of patients by clinicians through their own visual sense or patients’ self-report [2]. However, subjectivity and low-sensitivity are two main shortcomings of applying this routine way. Multiple clinicians may give different scores for the same patients. Besides, human visual system might not notice some tiny changes in the motor function of a patient. Sometimes, such assessment approaches may be verbose. For instance, it would take a long time to use the Fugl-Meyer (FM) assessment scale for rating the level of motor function because it consists of 50 items examining mainly fine motor skills [2]. An added shortcoming is that the evaluation needs to be operated by professionals, indicating its inability to be implemented anytime and anywhere, especially for home or community use. Therefore, there have been increasing demands for developing effective approaches to evaluate motor function in an objective and convenient way. These approaches would have motor function measurable in numerical terms by applying motion capture technique, which could facilitate the evaluation approach and enable monitoring for outcomes of clinical interventions during the rehabilitation process.The key to achieve the quantitative evaluation of motor function is to sense the motion of human body so as to analyze motion abnormalities. In terms of the sensing technology employed to capture motion data, a variety of reported approaches can be summarized into several categories, including techniques based on computer vision (i.e., cameras), inertial sensors, pressure sensors and electromyography (EMG) sensors, respectively. The computer vision-based techniques interpret motions by the means of acquiring, processing, analyzing, and understanding images of human body movements [3,4,5,6,7]. For example, the Vicon system consisting of multiple infrared high-speed cameras and an associated software can be used to capture the motion data [3], for gait analysis and even the motor function evaluation [4,5]. However, site-specific constraint limits wide applications of the computer vision-based techniques. The inertial sensors such as accelerometer, gyroscope, or combination of both termed as inertial measurement unit (IMU), can capture kinematic information about the body movement when placed over appropriate body parts [8,9,10]. Some studies reported successful applications of the accelerometers in monitoring the daily living ability of stoke survivors [11,12,13]. However, in these studies, participants needed to wear accelerometers for a long time like 24 h or even 3 days during the active/inactive periods. Patel et al. [14] purposefully selected eight tasks from the Function Ability Scale and gave each task an estimated score through pattern recognition analyses of the accelerometer data. Gubbi et al. [15] developed an approach to calculate an index equivalent to the National Institute of Health Stroke Score (NIHSS) motor index of stroke patients by measuring the acceleration of the arms. Pressure sensor can be used to offer supplementary kinematic information in terms of the imposed pressure. It has been already used in many studies involving gait analysis [16]. The surface EMG sensor is able to measure electrical potentials generated from muscle contractions in a nonintrusive way [17]. Therefore, the EMG-based techniques have been widely used for context awareness [17], motor control analysis [18], rehabilitation training [19], and motion pattern recognition and interaction [20,21,22,23,24,25].Recently, a series of sensors like pressure sensors, IMUs and EMG sensors have been embedded in many smart devices with capability of movement sensing due to their low-cost, wearable and self-contained features. Meanwhile, multi-source data fusion technique has become a very popular research topic in many fields, such as gait analysis [9,16], motion pattern recognition [20,21,22,23,24,25], and movement monitoring [26,27,28]. The combination of both IMU and EMG sensor has been found to take advantage of complementary information that help enhance performance of gestural control [20,21,22,23,24,25] and motor function assessment for people with disabilities [27,28]. However, the development of motor function assessment relying on fusion of wearable sensors is still insufficient.In this paper, a novel framework for upper-limb motor function assessment was proposed based on information fusion of wearable IMU and surface EMG sensors. A set of 11 canonical tasks was specifically designed for subjects to perform during the test, and meanwhile a series of unsupervised and supervised machine learning algorithms were accordingly applied to the recorded motion data. Given the data from healthy subjects, the normal pattern of the task performance was established as standard reference. Therefore, for a given subject, the upper limb motor function was quantified by evaluation indicators representing the degree of motor abnormality with respect to that normal reference. The study can be regarded as an evolution of our recently reported gestural sensing technology [20,21,22,23] using combined IMU and EMG sensors toward motor function evaluation as well as clinical outcome measurement. The feasibility of the proposed framework was indeed demonstrated with data from hemi-paretic stroke survivors.

2. Materials and Methods

2.1. Sensing Devices

In order to capture upper-limb movements, a home-made sensing system consisting of two IMUs and 10 surface EMG sensors in total was used for data collection in this study. In the system, multiple separate sensing devices were designed in a wrist-band or arm-band formation to ensure its wearability. In this study, one wrist-band and two arm-bands (placed over both upper-arm and forearm) were employed for sensing movements of the upper-limb including subtle fingers, wrist, elbow and shoulder, as shown in Figure 1, where the right arm was used as an example. One IMU (MPU-9250, InvenSense, San Jose, CA, USA; including a 3-axis ACC and a 3-axis GYRO, denoted as IMU1) was embedded in the wristband, located at the middle of the back of the forearm. A round reference electrode (Dermatrode; American Imex, Irvine, CA, USA) was also placed within the wristband over the front side of the forearm. The forearm band consisted of eight surface EMG sensors, evenly distributed around the maximal circumference of the forearm cross-section. The EMG sensor #1, #3, #5 and #7 were place over the central line of the anterior side, the ulnar side, the central line of the posterior side and the radial side of the forearm. For the upper-arm band, two EMG sensors targeting at the biceps brachii and the triceps brachii muscles respectively were embedded in the inner side of a stretchable belt, while an IMU (denoted as IMU2) attached on the opposite side of the belt to the surface EMG sensor over the biceps. The stretchability of these bands ensured the sensors remained firmly fixed at their targeted positions. Besides, the sensor-placement on the left was symmetrical with that on the right one. Each surface EMG sensor included two parallel bar-shaped dry electrodes (1 mm × 10 mm, with 10 mm center-to-center distance) to constitute a single-differential recording channel. In this system, the signal of each EMG channel was amplified with a gain of 600 in total and further digitized by a 12-bit A/D converter (ADS1198, Texas Instruments, Dallas, TX, USA). The sampling rate of each EMG channel was 1000 Hz. The IMU was able to produce digitalized data with a sampling rate of 100 Hz for each axis. All the recorded data were wirelessly transmitted to a computer. This study used a laptop computer to store the data into its hard disk for off-line analysis in a Matlab environment (version 2014a, The Mathworks Inc., Natick, MA, USA).

Sensors 17 00582 g001 550
Figure 1. Schematic of the placement and orientation of the sensors in the experiment. The right upper limb is taken as an example to illustrate here. The red ones stand for EMG sensors, and the blue ones stand for IMUs. IMU’s z-axis is perpendicular outside to the plan.


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[Abstract] Reliability of and Minimal Detectable Changes in Gait Performance Tests in Patients With Chronic Hemiplegic Stroke


Purpose: This study aimed to determine the inter- and intra-rater reliability of and minimal detectable changes (MDCs) at the 95% confidence interval in gait performance tests in patients with chronic hemiplegic stroke who can walk independently.

Materials and Methods: Thirty patients with chronic hemiplegic stroke (24 men, 6 women, mean age 62.5 ± 11.6 years) were enrolled. Physical therapists (mean clinical experience: 9.1 ± 9.3 years) performed the timed up and go test (TUG), 10-m walk test (10MWT), and 6-min walk test (6MWT) 1 day apart. Reliability was evaluated using the intraclass correlation coefficient (ICC) and Bland–Altman analysis.

Results: The ICC was ≥0.9 for all tests, and no systematic bias was found. MDC at the 95% confidence interval was 1.9 s for the TUG, 0.16 m/s for the 10MWT, and 28.4 m for the 6MWT.

Discussion: We demonstrated excellent intra- and inter-rater reliability of all tests. These results suggest that gait performance tests are reliable.

Conclusion: These commonly used gait performance tests demonstrated high reliability and can be recommended to evaluate clinically meaningful improvements in patients with chronic hemiplegic stroke who can walk independently.

via Reliability of and Minimal Detectable Changes in Gait Performance Tests in Patients With Chronic Hemiplegic Stroke – Jun Hayakawa, Mitsuhiro Ochi, Yudai Yano, Ryutaro Matsugaki, Yuto Ogata, Takeshi Murakami, Satoshi Kuhara, Hideaki Itoh, Kenji Hachisuka, Satoru Saeki, 2020

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[ARTICLE] Pilot Study of a Powered Exoskeleton for Upper Limb Rehabilitation Based on the Wheelchair – Full Text


To help hemiplegic patients with stroke to restore impaired or lost upper extremity functionalities efficiently, the design of upper limb rehabilitation robotics which can substitute human practice becomes more important. The aim of this work is to propose a powered exoskeleton for upper limb rehabilitation based on a wheelchair in order to increase the frequency of training and reduce the preparing time per training. This paper firstly analyzes the range of motion (ROM) of the flexion/extension, adduction/abduction, and internal/external of the shoulder joint, the flexion/extension of the elbow joint, the pronation/supination of the forearm, the flexion/extension and ulnar/radial of the wrist joint by measuring the normal people who are sitting on a wheelchair. Then, a six-degree-of-freedom exoskeleton based on a wheelchair is designed according to the defined range of motion. The kinematics model and workspace are analyzed to understand the position of the exoskeleton. In the end, the test of ROM of each joint has been done. The maximum error of measured and desired shoulder flexion and extension joint angle is 14.98%. The maximum error of measured and desired elbow flexion and extension joint angle is 14.56%. It is acceptable for rehabilitation training. Meanwhile, the movement of drinking water can be realized in accordance with the range of motion. It demonstrates that the proposed upper limb exoskeleton can also assist people with upper limb disorder to deal with activities of daily living. The feasibility of the proposed powered exoskeleton for upper limb rehabilitation training and function compensating based on a wheelchair is proved.

1. Introduction

Upper extremity motor function disorder is one of the most common rehabilitation problems of hemiplegic patients with stroke [1]. The upper extremity motor function plays a key role in self-care and social activities. The upper extremity motor function disorder significantly lowers the life quality of hemiplegic patients with stroke [23]. Due to the complex structure and functional requirement of the upper limb, the rehabilitation process of the impaired upper extremity functionality is a long and slow process. Because of the specificity of hemiplegic patients in diagnosis, treatment, and rehabilitation, it brings a series of severe psychological and financial stress for patients [4]. The outcome of upper limb motor rehabilitation depends on duration, intensity and task orientation of the training. The therapists assisting patients have to bear a significant burden. As a result, the duration of primary upper limb rehabilitation is becoming shorter [5]. To deal with these problems, robotic rehabilitation devices with the ability to conduct repetitive tasks and provide assistive force have been proposed.

The upper limb rehabilitation robots can be divided into two types according to the service environment. One is mainly used in the hospital and shared by several patients. The upper limb rehabilitation robots used in the hospital are often designed for rehabilitation training and difficult to move. Loris et al. introduced a dual exoskeleton robot called automatic recovery arm motility integrated system. The system was developed to enable therapists to define and apply patient-specific rehabilitation exercises with multidisciplinary support by neurologist, engineers, ICT specialists and designers [6]. Farshid et al. presented the GENTLE/S system for upper limb rehabilitation. The system comprised a 3-degree-of-freedom (DOF) robot manipulator with an extra 3 DOFs passive gimbal mechanism, an exercise table, computer screen, overhead frame, and chair [7]. Dongjin Lee et al. proposed a clinically relevant upper-limb exoskeleton that met the clinical requirements. The pilot test showed that the safety for robot-aided passive training of patients with spasticity could be guaranteed [8]. The other is mainly used in the home to assist a single patient in activities of daily living. A lightweight and ergonomic upper-limb rehabilitation exoskeleton named CLEVER ARM was proposed by Zeiaee et al. The wearable upper limb exoskeleton was to provide automated therapy to stroke patients [9]. Feiyun et al. presented a seven DOFs cable-driven upper limb exoskeleton for post-stroke patients. The experimental results showed that the activation levels of corresponding muscles were reduced by using the 7 DOFs cable-driven upper limb exoskeleton in the course of rehabilitation [10]. In fact, the main function of upper extremity rehabilitation devices is to provide the physical training and assist the patients with hemiplegia to perform the activities of daily living. However, hospital or home used rehabilitation robot research has just focused on one respect. Indeed, the research on the upper extremity rehabilitation devices would focus on both aspects of assisting and training. Therefore, it is important for the design of upper limb rehabilitation robot to combine the rehabilitation training and assisting function.

The stationary upper extremity rehabilitation robot cannot solve the movability problem and perform the activities of daily living (ADL). The wearable exoskeleton devices are limited by the weight. In addition, whether the range of motion is in line with the physiological joints directly determines the rehabilitation effect. Therefore, the key questions can be summarized as follows. Can we transform the weight of the upper limb exoskeleton to another movable device instead of wearing by patients? How to guarantee the design of upper limb exoskeleton joint axis in line with the human joint movement axis?

To deal with the above questions, some researchers have made useful explorations. Kiguchi et al. proposed a mechanism and control method of a mobile exoskeleton robot based on a wheelchair for 3 DOFs upper-limb motion assist [11]. The first problem of transforming weight can be solved by design based on a wheelchair. The physical rehabilitation training can be realized on a wheelchair instead of a stationary place. The ADL can be assisted by the powered upper limb exoskeleton on a moving platform. However, the rotation axis of each joint (shoulder joint and elbow joint) is moving with the movement of the upper limb. The gap between the exoskeleton and human arm is also changing by following their movement. It does not consider the problem about the movement consistency of the exoskeleton joint rotation axis and the human joint. As for this problem, Vitiello et al. proposed an elbow exoskeleton with double-shelled links to allow an ergonomic physical human-robot interface and a four-degree-of-freedom passive mechanism to allow the user’s elbow and robot axes to be constantly aligned during movement [12]. However, it focused on the elbow. The whole upper limb rehabilitation was not considered. In this work, we present a novel solution for the two mentioned problems. The range of motion of the upper extremity exoskeleton based on a wheelchair is defined through the normal people test. The 6 DOFs exoskeleton based on a wheelchair is designed according to the defined range of motion. The pursuit movement experiment and the assistive movement of drinking water of the prototype are done to verify the feasibility of the design.

2. Materials and Methods

2.1. Definition of ROM of Each Joint for the Specific Upper Limb Exoskeleton on a Wheelchair

To ensure the safety of using an upper limb exoskeleton on a wheelchair, it is necessary to know the ROM of the human upper limb on the wheelchair.

The parts of the upper limb taken into account in the design of an exoskeleton are shoulder, arm, elbow, wrist, and hand. Hand is excluded in an entire upper extremity exoskeleton design because of its complexity and dexterous characteristic. Therefore, this work only analyzes the ROM of the shoulder joint, elbow joint, and wrist joint. And then the upper limb exoskeleton designed in this paper must conform to the ROM of these joints.

2.1.1. Apparatus

The apparatus consists of a wheelchair and a motion analysis system. The motion analysis system can transmit data in real time. It was made in JIANGSU NEUCOGNIC MEDICAL CO., LTD. The system can measure the ROM of the shoulder joint, elbow joint and wrist joint of a person who sits on a common wheelchair. In Figure 1, there are two inertial sensors located at the upside and downside of backbone, and ten inertial sensors located at the upper limb (shoulder, upper arm, forearm, palm, and hand), respectively. All of the sensors in this system can measure the angles in x-, y– and z-axis. Sensor 1 and Sensor 4 are utilized to measure the ROM of the rear waist as the referring data. Sensor 4 and Sensor 6 are utilized to measure the ROM of the shoulder joint as the referring data. Sensor 6 and Sensor 7 are utilized to measure the ROM of the elbow joint as the referring data. Sensor 7 and hand sensor are utilized to measure the ROM of wrist joint as the referring data.[…]

Continue —-> Pilot Study of a Powered Exoskeleton for Upper Limb Rehabilitation Based on the Wheelchair

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[Abstract] Optimizing Hand Rehabilitation Post-Stroke Using Interactive Virtual Environments

The main goal of this project is to refine and optimize elements of the virtual reality-based training paradigms to enhance neuroplasticity and maximize recovery of function in the hemiplegic hand of patients who had a stroke.

PIs, Sergei Adamovich, Alma Merians, Eugene Tunik, A.M. Barrett

This application seeks funding to continue our on-going investigation into the effects of intensive, high dosage task and impairment based training of the hemiparetic hand, using haptic robots integrated with complex gaming and virtual reality simulations. A growing body of work suggests that there is a time-limited period of post-ischemic heightened neuronal plasticity during which intensive training may optimally affect the recovery of gross motor skills, indicating that the timing of rehabilitation is as important as the dosing. However, recent literature indicates a controversy regarding both the value of intensive, high dosage as well as the optimal timing for therapy in the first two months after stroke. Our study is designed to empirically investigate this controversy. Furthermore, current service delivery models in the United States limit treatment time and length of hospital stay during this period. In order to facilitate timely discharge from the acute care hospital or the acute rehabilitation setting, the initial priority for rehabilitation is independence in transfers and ambulation. This has negatively impacted the provision of intensive hand and upper extremity therapy during this period of heightened neuroplasticity. It is evident that providing additional, intensive therapy during the acute rehabilitation stay is more complicated to implement and difficult for patients to tolerate, than initiating it in the outpatient setting, immediately after discharge. Our pilot data show that we are able to integrate intensive, targeted hand therapy into the routine of an acute rehabilitation setting. Our system has been specifically designed to deliver hand training when motion and strength are limited. The system uses adaptive algorithms to drive individual finger movement, gain adaptation and workspace modification to increase finger range of motion, and haptic and visual feedback from mirrored movements to reinforce motor networks in the lesioned hemisphere. We will translate the extensive experience gained in our previous studies on patients in the chronic phase, to investigate the effects of this type of intervention on recovery and function of the hand, when the training is initiated within early period of heightened plasticity. We will integrate the behavioral, the kinematic/kinetic and neurophysiological aspects of recovery to determine: 1) whether early intensive training focusing on the hand will result in a more functional hemiparetic arm; (2) whether it is necessary to initiate intensive hand therapy during the very early inpatient rehabilitation phase or will comparable outcomes be achieved if the therapy is initiated right after discharge, in the outpatient period; and 3) whether the effect of the early intervention observed at 6 months post stroke can be predicted by the cortical reorganization evaluated immediately after the therapy. This proposal will fill a critical gap in the literature and make a significant advancement in the investigation of putative interventions for recovery of hand function in patients post-stroke. Currently relatively little is known about the effect of very intensive, progressive VR/robotics training in the acute early period (5-30 days) post-stroke. This proposal can move us past a critical barrier to the development of more effective approaches in stroke rehabilitation targeted at the hand and arm.

via Hand Rehabilitation Post Stroke

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[ARTICLE] EMG based FES for post-stroke rehabilitation – Full Text


Annually, 15 million in world population experiences stroke. Nearly 9 million stroke
survivors every year experience mild to severe disability. The loss of upper extremity function in stroke survivors still remains a major rehabilitation challenge. The proposed EMG based FES system can be used for effective upper limb motor re-education in post stroke upper limb rehabilitation. The  governing feature of the designed system is its synchronous activation, in which the FES stimulation is dependent on the amplitude of the EMG signal acquired from the unaffected upper limb muscle of the hemiplegic patient. This proportionate operation eliminates the undesirable  damage to the patient’s skin by generating stimulus in proportion to voluntary EMG signals. This feature overcomes the disadvantages of currently available manual motor re-education systems. This model can be used in home-based post stroke rehabilitation, to effectively improve the upper limb functions.


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[ARTICLE] Role of Practice And Mental Imagery on Hand Function Improvement in Stroke Survivors – Full Text


Objective: The purpose of this study was to evaluate the Role of Practice and Mental Imagery on Hand function improvement in stroke survivors

Method: We conducted systematic review of the previous studies and searched electronic databases for the years 1995 to 2016, studies were selected according to inclusion criteria, and critical appraisal was done for each study and summarized the use of mental practice for the improvement in hand function in stroke survivors.

Results: Studies differed in the various aspects like intervention protocols, outcome measures, design, and patient’s characteristics. The total number of practice hours to see the potential benefits from mental practice varied widely. Results suggest that mental practice has potential to improve the upper extremity function in stroke survivors.

Conclusion: Although the benefits of mental practice to improve upper extremity function looks promising, general guidelines for the clinical use of mental practice is difficult to make. Future research should explore the dosage, factors affecting the use of Mental Practice, effects of Mental Therapy alone without in combination with other interventions.


Up to 85% stroke survivors experience hemi paresis resulting in impaired movement of the arm, and hand as reported by Nakayama et al. Loss of arm function adversely affects quality of life and functional motor recovery in affected upper extremity.

Sensorimotor deficits in the upper limb, such as weakness, decreased speed of movement, decreased angular excursion and impaired temporal coordination of the joints impaired upper-limb and trunk coordination.

Treatment interventions such as materials-based occupations constraint-induced movement therapy modified constraint-induced movement therapy and task-related or task-specific training are common training methods for remediating impairments and restoring function in the upper limb.

For the improvement of upper and lower functions, physical therapy provides training for functional improvement and fine motor. For most patients such rehabilitation training has many constraints of time, place and expense, accordingly in recent studies, clinical methods such as mental practice for improvement of the upper and lower functions have been suggested.

Mental practice is a training method during which a person cognitively rehearses a physical skill using motor imagery in the absence of overt, physical movements for the purpose of enhancing motor skill performance. For example, a review of the duration of mental movements found temporal equivalence for reaching; grasping; writing; and cyclical activities, such as walking and running.

Evidence for the idea that motor imagery training could enhance the recovery of hand function comes from several lines of research: the sports literature; neurophysiologic evidence; health psychology research; as well as preliminary findings using motor imagery techniques in stroke patients.

Much interest has been raised by the potential of Motor Practice of Motor task, also called “Motor Imagery” as a neuro rehabilitation technique to enhance Motor Recovery following Stroke.

Mental Practice is a training method during which a person cognitively rehearsals a physical skill using Motor Imagery in the absence of Physical movements for the purpose of enhancing Motor skill performance.

The merits of this intervention are that the patient concentration and motivation can be enhanced without regard to time and place and the training is possible without expensive equipment.

Researchers have speculated about its utility in neurorehabilitation. In fact, several review articles examining the impact of mental practice have been published. Two reviews examined stroke outcomes in general and did not limit their review to upper-extremity–focused outcomes. Both articles included studies that were published in 2005 or earlier.

Previous reviews, however, did not attempt to rate the studies reviewed in terms of the level of evidence. Thus, in this review, we determined whether mental practice is an effective intervention strategy to remediate impairments and improve upper-limb function after stroke by examining and rating the current evidence. […]

Continue –>  Role of Practice And Mental Imagery on Hand Function Improvement in Stroke Survivors | Insight Medical Publishing

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[Abstract] A survey on sEMG control strategies of wearable hand exoskeleton for rehabilitation


Surface electromyographic (sEMG) signals is one most commonly used control source of exoskeleton for hand rehabilitation. Due to the characteristics of non-invasive, convenient collection and safety, sEMG can conform to the particularity of hemiplegic patients’ physiological state and directly reflect human’s neuromuscular activity. By way of collecting, analyzing and processing, sEMG signals corresponding to identify the target movement model would be translated into robot movement control instructions and input into hand rehabilitation exoskeleton controller. Then patients’ hand can be directed to achieve the realization of the similar action finally. In this paper, the recent key technologies of sEMG-based control for hand rehabilitation robots are reviewed. Then a summarization of controlling technology principle and methods of sEMG signal processing employed by the hand rehabilitation exoskeletons is presented. Finally suitable processing methods of multi-channel sEMG signals for the controlling of hand rehabilitation exoskeleton are put forward tentatively and the practical application in hand exoskeleton control is commented also.

Source: A survey on sEMG control strategies of wearable hand exoskeleton for rehabilitation – IEEE Xplore Document

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[Abstract] Gaming-based virtual reality therapy for the rehabilitation of upper extremity function after stroke.


Objective To investigate the effects of playing virtual reality games on the recovery of hemiplegic upper extremities after stroke.

Methods Thirty stroke patients with hemiplegic upper extremities were randomly assigned to a treatment group (n=15) or a control group (n=15).Both groups received routine medication and conventional physical therapy,while the treatment group was additionally given (Nintendo) gaming-based virtual reality therapy.Before and after 2 weeks of treatment,the patients in both groups were evaluated using the Fugl-Meyer Assessment for the Upper Extremities (FMA-UE),Brunnstrom staging and co-contraction ratios (CRs).Surface electromyogram signals from the biceps brachii and triceps brachii were also recorded during maximum isometric voluntary flexion and extension of the affected elbow.

Results No significant differences in any of the measurements were observed between the 2 groups before or after the intervention.Both groups demonstrated significant increases in their average FMA-UE score,Brunnstrom staging and CRs.

Conclusions Virtual reality gaming using a Wii controller is as effective as conventional therapy in enhancing upper extremity motor function and elbow flexion and extension after stroke.

Source: Gaming-based virtual reality therapy for the rehabilitation of upper extremity function after stroke | BVS Violência e Saúde

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[Abstract] Effectiveness of Bilateral Arm Training for Improving Extremity Function and Activities of Daily Living Performance in Hemiplegic Patients


Bilateral movement therapy, which encourages simultaneous use of the limbs on both the affected and nonaffected sides, is known to help in motor function recovery in hemiplegic patients. However, studies on the effectiveness of bilateral arm training for improving upper limb function and activities of daily living (ADL) performance in hemiplegic stroke patients are lacking. The present study investigated the effectiveness of bilateral arm training for improving upper limb function and ADL performance in hemiplegic stroke patients.


The study included 30 hemiplegic stroke patients. The patients were randomly divided into an experimental group (n = 15) and a control group (n = 15). All patients received a uniform general occupational therapy session lasting 30 minutes 5 times a week for 8 weeks. The experimental group received an additional session of bilateral arm training lasting 30 minutes, and the control group received an additional session of general occupational therapy lasting 30 minutes. The Fugl-Meyer assessment (FMA), Box and Block Test (BBT), and modified Barthel index (MBI) were used for evaluation.


In both the experimental and control groups, the FMA, BBT, and MBI scores were significantly higher after the intervention than before the intervention (P <.05). The changes in the FMA, BBT, and MBI scores were greater in the experimental group than in the control group (P <.05).


Bilateral arm training along with general occupational therapy might be more effective than occupational therapy alone for improving upper limb function and ADL performance in hemiplegic stroke patients.

Source: Effectiveness of Bilateral Arm Training for Improving Extremity Function and Activities of Daily Living Performance in Hemiplegic Patients – Journal of Stroke and Cerebrovascular Diseases

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