Posts Tagged upper limb

[ARTICLE] Enabling Stroke Rehabilitation in Home and Community Settings: A Wearable Sensor-Based Approach for Upper-Limb Motor Training – Full Text

A conceptual representation of the wrist-worn sensor system for home-based upper-limb rehabilitation. The system consists of two wearable sensors, a tablet computer to be… View more

Abstract:

High-dosage motor practice can significantly contribute to achieving functional recovery after a stroke. Performing rehabilitation exercises at home and using, or attempting to use, the stroke-affected upper limb during Activities of Daily Living (ADL) are effective ways to achieve high-dosage motor practice in stroke survivors. This paper presents a novel technological approach that enables 1) detecting goal-directed upper limb movements during the performance of ADL, so that timely feedback can be provided to encourage the use of the affected limb, and 2) assessing the quality of motor performance during in-home rehabilitation exercises so that appropriate feedback can be generated to promote high-quality exercise. The results herein presented show that it is possible to detect 1) goal-directed movements during the performance of ADL with a c -statistic of 87.0% and 2) poorly performed movements in selected rehabilitation exercises with an F -score of 84.3%, thus enabling the generation of appropriate feedback. In a survey to gather preliminary data concerning the clinical adequacy of the proposed approach, 91.7% of occupational therapists demonstrated willingness to use it in their practice, and 88.2% of stroke survivors indicated that they would use it if recommended by their therapist.

Introduction

Stroke is a leading cause of severe long-term disability. In the US alone, nearly 800,000 people suffer a stroke each year [1]. The number of individuals who suffer a stroke each year is expected to rise in the coming years because the prevalence of stroke increases with age and the world population is aging [2]. Approximately 85% of individuals who have a stroke survive, but they often experience significant motor impairments. Upper-limb paresis is the most common impairment following a stroke. It affects 75% of stroke survivors and leads to limitations in the performance of Activities of Daily Living (ADL) [4].

Inability to use the stroke-affected upper limb for ADL often leads to a phenomenon that is referred to as learned non-use [5]. As patients rely more and more on the unaffected (or less impaired) upper limb [5] they progressively lose motor abilities of the stroke-affected upper limb that they may have recovered as a result of a rehabilitation intervention [6].

A high dosage of motor practice using the stroke-affected upper limb during the performance of ADL, despite considerable difficulty, stimulates neuroplasticity and motor function recovery [7]–[8][9]. Thus, it is clinically important to encourage stroke survivors to continue making appropriate use of the affected upper limb [10]–[11][12][13], in addition to engaging in rehabilitation exercises that focus on range-of-motion and functional abilities [14]–[15][16].

The use of wearable sensors has recently emerged as an efficient way to monitor the amount of upper-limb use after a stroke [17]–[18][19][20][21][22]. However, despite growing evidence of the clinical potential of these devices [23], their widespread clinical deployment has been hindered by technical limitations. A shortcoming of currently available wrist-worn devices is that they cannot distinguish between Goal-Directed (GD) movements (i.e., movements performed for a specific purposeful task) and non-Goal-Directed (non-GD) movements (e.g., the arm swinging during gait). Instead, these sensors focus on recording the number and/or intensity of any type of arm movements [10]. Consequently, non-GD movements are reflected as part of the measurements with equal importance as GD movements. This results in an overestimation of the amount of actual arm use [24]. Furthermore, monitoring the aggregate number of stroke-affected upper limb movements is not sufficient for the purpose of providing timely feedback to encourage the use of the affected limb during the performance of ADL. To promote the use of the stroke-affected limb, it is critical that feedback reflects the relative use of the affected upper limb compared to the contralateral one.

Wrist-worn movement sensors have also been applied to monitoring rehabilitation exercises in the home setting [25]–[26][27][28]. However, existing systems primarily focus on quantifying the dosage/intensity of the exercises (e.g., the duration of the exercises and the number of movement repetitions) and do not monitor if the quality of the performed exercise is appropriate. Ensuring good quality of movement during the performance of rehabilitation exercises is critical for maximizing functional recovery after a stroke [29]. Moreover, providing customized feedback regarding the quality of exercise movements can increase motivation, promote long-term adherence to a prescribed exercise regimen, and ultimately maximize clinical outcomes [30]. One of the reasons for limited exercise participation by stroke survivors is the lack of access to resources to support exercise including performance feedback from rehabilitation specialists [31]. There are no technical solutions that provide feedback regarding the quality of exercise performance for upper-limb rehabilitation after stroke.

We propose a system for aiding in functional recovery after a stroke that consists of two wearable sensors, one worn on the stroke-affected upper limb and the other on the contralateral upper limb [32] (Fig. 1). The proposed system can be used to provide timely feedback when ADL are performed. If the system detects that the patient consistently performs GD movements with the unaffected upper limb, and rarely uses the stroke-affected upper limb, then a visual or vibrotactile reminder can be triggered to encourage the patient to attempt GD movements with the stroke-affected limb. A benefit of this approach is that if a movement is critical (e.g., signing a check), patients can use the unaffected upper limb without receiving negative feedback as long as they have performed a sufficient number of movements with the affected upper limb throughout the day. Furthermore, the system promotes high-dosage motor practice with appropriate feedback to extend components of rehabilitation interventions into the home environment.[…]

via Enabling Stroke Rehabilitation in Home and Community Settings: A Wearable Sensor-Based Approach for Upper-Limb Motor Training – IEEE Journals & Magazine

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[Abstract+References] The Use of Image Processing Methods to Improve the Detection of User’s Hand in Vision Based Games Used in Neurological Rehabilitation

Abstract

Vision based games is a type of software that can become a promising, modern neurorehabilitation tool. This paper presents the possibilities offered for the implementation of this kind of software by the open source vision library. The methods and functions related to the aspect of image processing and analysis are presented in terms of their usefulness in creating programs based on the analysis of the images acquired from the camera. On the basis of the issues contained in the paper, the functionality of the library is presented in terms of the possibilities related primarily to the processing of video sequences, detection, tracking and analysis of the movement of objects.

As part of the work, the software that meets the requirements for modern neurorehablitation games has been implemented. Its main part is responsible for the identification of the current position of the user’s hand and is based on the image captured from the webcam. Whereas the tasks set for the user used among others supporting visual-motor coordination.

The main subject of the research was the analysis of the impact of the applied methods of initial image processing on the correctness of the chosen tracking algorithm. It was proposed and experimentally examined the impact of operations such as morphological transformations or apply an additional mask on a functioning of the CamShift algorithm.  And hence on the functioning of the whole game which analyzing the user’s hand movement.

References

Allen G. J., Richard Xu Y. D., Jin J. S. (2004). Object Tracking Using CAMShift Algorithm and Multiple Quantized Feature Spaces, Proceedings of the Pan-Sydney area workshop on Visual information processing , Sydney, 3-7.

Bradski G., Kaehler A. (2008). Learning OpenCV. Computer Vision with the OpenCV Library, Sebastopol, CA: O’Reilly Media.

Buczyński P. (2005). Optymalna reprezentacja kolorów w analizie i przetwarzaniu obrazów komputerowych, Praca doktorska. Warszawa: Politechnika Warszawska.

Burke J. W., Morrow P.J., et al. (2008). Vision Based Games for Upper-Limb Stroke Rehabilitation, Machine Vision and Image Processing Conference, 159 – 164.

Burke J. W. McNeill M. D. J., et al. (2010). Designing engaging, playable games for rehabilitation”, International Conference Series On Disability, Virtual Reality and Associated Technologies (ICDVRAT), 195-202.

Cameirão M.S. , et al. (2010). Neurorehabilitation using the virtual reality based Rehabilitation Gaming System: methodology, design, psychometrics, usability and validation, Journal of NeuroEngineering and Rehabilitation, 7, 48.

Comaniciu D., Ramesh V., Meer P. (2003). Kernel-based object tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions 2003, p. 564-577.

Derpanis K. G. (2005). Mean Shift Clustering, http://www.cse.yorku.ca/~kosta/ Comp-Vis_Notes/mean_shift.pdf

Di Loreto I., Gouaich A., Hocine N., (2011). Mixed reality serious games for post-stroke rehabilitation, Pervasive Computing Technologies for Healthcare , 5th International Conference on, 530-537.

Garcia-Marin J., Felix-Navarro K., Law-rence E. (2011). Serious games to Improve the Physical Health of the Elderly: A Categorization Scheme, Fourth International Conference on Advances in Human-oriented and Personalized Mechanisms, Technologies, and Services (CENTRIC 2011), 64-71.

Jog A., Halbe S. (2013). Multiple Objects Tracking Using CAMShift Algorithm and Implementation of Trip Wire, International Journal of Image, Graphics and Signal Processing, 43-48.

Joshi S., Gujarathi S., Mirgemoving A. (2014). Moving object tracking method using improved camshift with surf algorithm. International Journal of Advances in Science Engineering and Technology, 2(2), 14-19.

Laganière R. (2011). “OpenCV 2 Computer Vision Application Programming Cookbook”, Packt Publishing, 2011.

Lange B., Flynn S.M., Rizzo A. A., (2009). Game-based telerehabilitation, European Journal of Physical and Rehabilitation Medicine, 45(1), 143-151.

Rafajłowicz E, Rafajłowicz W. (2010). Wstęp do przetwarzania obrazów przemysłowych, Wrocław: Oficyna Wydawnicza Politechniki Wrocławskiej.

Rayavel P., Appasami G., Nakeeran R. (2011). Noise removal for object tracking based on HSV color space parameter using CAMSHIFT. International Journal of Computational Intelligence & Telecommunication Systems, 2(1), 39–45.

Yilmaz A., Javed O., Shah M. (2006). Object tracking: A survey, ACM Computing Surveys, 38(4), Article 13, 1-45.

 

via The Use of Image Processing Methods to Improve the Detection of User’s Hand in Vision Based Games Used in Neurological Rehabilitation | Gospodarek | IMAGE PROCESSING & COMMUNICATIONS

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[ARTICLE] BCI-Based Strategies on Stroke Rehabilitation with Avatar and FES Feedback – Full Text PDF

Stroke is the leading cause of serious and long-term disability worldwide. Some studies have shown that motor imagery (MI) based BCI has a positive effect in poststroke rehabilitation. It could help patients promote the reorganization processes in the damaged brain regions. However, offline motor imagery and conventional online motor imagery with feedback (such as rewarding sounds and movements of an avatar) could not reflect the true intention of the patients. In this study, both virtual limbs and functional electrical stimulation (FES) were used as feedback to provide patients a closed-loop sensorimotor integration for motor rehabilitation. The FES system would activate if the user was imagining hand movement of instructed side. Ten stroke patients (7 male, aged 22-70 years, mean 49.5+-15.1) were involved in this study. All of them participated in BCI-FES rehabilitation training for 4 weeks.The average motor imagery accuracies of the ten patients in the last week were 71.3%, which has improved 3% than that in the first week. Five patients’ Fugl-Meyer Assessment (FMA) scores have been raised. Patient 6, who has have suffered from stroke over two years, achieved the greatest improvement after rehabilitation training (pre FMA: 20, post FMA: 35). In the aspect of brain patterns, the active patterns of the five patients gradually became centralized and shifted to sensorimotor areas (channel C3 and C4) and premotor area (channel FC3 and FC4).In this study, motor imagery based BCI and FES system were combined to provided stoke patients with a closed-loop sensorimotor integration for motor rehabilitation. Result showed evidences that the BCI-FES system is effective in restoring upper extremities motor function in stroke. In future work, more cases are needed to demonstrate its superiority over conventional therapy and explore the potential role of MI in poststroke rehabilitation.

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via [1805.04986] BCI-Based Strategies on Stroke Rehabilitation with Avatar and FES Feedback

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[Abstract+References] Self-directed therapy programmes for arm rehabilitation after stroke: a systematic review

To investigate the effectiveness of self-directed arm interventions in adult stroke survivors.

A systematic review of Medline, EMBASE, CINAHL, SCOPUS and IEEE Xplore up to February 2018 was carried out. Studies of stroke arm interventions were included where more than 50% of the time spent in therapy was initiated and carried out by the participant. Quality of the evidence was assessed using the Cochrane risk of bias tool.

A total of 40 studies (n = 1172 participants) were included (19 randomized controlled trials (RCTs) and 21 before–after studies). Studies were grouped according to no technology or the main additional technology used (no technology n = 5; interactive gaming n = 6; electrical stimulation n= 11; constraint-induced movement therapy n = 6; robotic and dynamic orthotic devices n = 8; mirror therapy n = 1; telerehabilitation n = 2; wearable devices n = 1). A beneficial effect on arm function was found for self-directed interventions using constraint-induced movement therapy (n = 105; standardized mean difference (SMD) 0.39, 95% confidence interval (CI) −0.00 to 0.78) and electrical stimulation (n = 94; SMD 0.50, 95% CI 0.08–0.91). Constraint-induced movement therapy and therapy programmes without technology improved independence in activities of daily living. Sensitivity analysis demonstrated arm function benefit for patients >12 months poststroke (n = 145; SMD 0.52, 95% CI 0.21–0.82) but not at 0–3, 3–6 or 6–12 months.

Self-directed interventions can enhance arm recovery after stroke but the effect varies according to the approach used and timing. There were benefits identified from self-directed delivery of constraint-induced movement therapy, electrical stimulation and therapy programmes that increase practice without using additional technology.

References

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via Self-directed therapy programmes for arm rehabilitation after stroke: a systematic review – Ruth H Da-Silva, Sarah A Moore, Christopher I Price, 2018

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[Abstract] Adaptive integral terminal sliding mode control for upper-limb rehabilitation exoskeleton

Highlights

    Adaptive integral sliding mode control design for exoskeletons.

    Finite time convergence of the closed-loop system.

    Robustness of the control law with respect to parametric variations and disturbances.

    No requirement of the knowledge of the system bounds.

    Real experiments using an upper limb exoskeleton with and without human subjects.

Abstract

A robust adaptive integral terminal sliding mode control strategy is proposed in this paper to deal with unknown but bounded dynamic uncertainties of a nonlinear system. This method is applied for the control of upper limb exoskeleton in order to achieve passive rehabilitation movements. Indeed, exoskeletons are in direct interaction with the human limb and even if it is possible to identify the nominal dynamics of the exoskeleton, the subject’s limb dynamics remain typically unknown and defer from a person to another. The proposed approach uses only the exoskeleton nominal model while the system upper bounds are adjusted adaptively. No prior knowledge of the exact dynamic model and upper bounds of uncertainties is required. Finite time stability and convergence are proven using Lyapunov theory. Experiments were performed with healthy subjects to evaluate the performance and the efficiency of the proposed controller in tracking trajectories that correspond to passive arm movements.

 

via Adaptive integral terminal sliding mode control for upper-limb rehabilitation exoskeleton – ScienceDirect

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[ARTICLE] Interactive Design and Development of Real Arm Movements for Application in Rehabilitation – Full Text PDF

Abstract

An interactive real arm movements for application in rehabilitation is designed and
developed. The aim is to encourage hand paralysis patients performing their physical therapy by introducing games application in replacing conventional hand therapy module and methods. In this project, the accelerometer is used for tracking the orientation of the arm. As the arm moves, the values from x, y and z axis from the accelerometer changes and are being read by the Analog Inputs of the Arduino Board. After being read by the Analog Inputs of the Arduino Board, the 3D model moves as well. Solidworks software was used to modeled the hand in which the data is then transferred to Matlab/Simulink using SimMechanicalLink from Mathworks. Lastly, the sensor glove was programmed to work as a controller of games application in hand rehabilitation thus makes it an enjoyable therapy process. […]

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[Abstract] Pain-related psychological issues in hand therapy

Highlights

  • Pain is a subjective experience that results from the complex modulation of nociception conveyed to the brain via the nervous system.
  • Psychological factors such as cognitions (eg, pain catastrophizing), emotions (eg, depression), and pain-related behaviors (eg, avoidance) can influence perceived pain intensity, physical function, and treatment outcomes.
  • Several evidence-based interventions to address pain-related psychological risk factors are available and can be integrated into hand therapy.

Abstract

Study Design

Literature review.

Introduction

Pain is a subjective experience that results from the modulation of nociception conveyed to the brain via the nervous system. Perception of pain takes place when potential or actual noxious stimuli are appraised as threats of injury. This appraisal is influenced by one’s cognitions and emotions based on her/his pain-related experiences, which are processed in the forebrain and limbic areas of the brain. Unarguably, patients’ psychological factors such as cognitions (eg, pain catastrophizing), emotions (eg, depression), and pain-related behaviors (eg, avoidance) can influence perceived pain intensity, disability, and treatment outcomes. Therefore, hand therapists should address the patient pain experience using a biopsychosocial approach. However, in hand therapy, a biomedical perspective predominates in pain management by focusing solely on tissue healing.

Purpose of the Study

This review aims to raise awareness among hand therapists of the impact of pain-related psychological factors.

Methods and Results

This literature review allowed to describe (1) how the neurophysiological mechanisms of pain can be influenced by various psychological factors, (2) several evidence-based interventions that can be integrated into hand therapy to address these psychological issues, and (3) some approaches of psychotherapy for patients with maladaptive pain experiences.

Discussion and Conclusion

Restoration of sensory and motor functions as well as alleviating pain is at the core of hand therapy. Numerous psychological factors including patients’ beliefs, cognitions, and emotions alter their pain experience and may impact on their outcomes. Decoding the biopsychosocial components of the patients’ pain is thus essential for hand therapists.

via Pain-related psychological issues in hand therapy – Journal of Hand Therapy

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[WEB SITE] Project3 – Flexo-glove

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Project Description

Flexo-glove is a 3D printed soft exoskeleton robotic glove with compact and streamlined design for assistance in activities of daily livings and rehabilitation purposes of patients with hand function impairment.

Specifications:

  • Overall weight of 330g including battery
  • Providing 22N pinch force, 48N power grasp force and object grasp size of up to 81mm in diameter
  • Two control modes: intention-sensing via wireless surface EMG for assistive mode and externally-directed via an accompanying smartphone

Project Details: —> Visit site

My Role:

  • Initiated the project with the idea of using soft 3D printed materials in design of the Flexo-glove inspired by X-Limb
  • Performed feasibility study for using cable-driven mechanism in actuation of rehabilitation glove
  • Leading a group of four mechatronics engineering students to fabricate the prototype and characterise the grip forces

Awards

  • Received Dyason fellowship, $5000 travel fellowship awarded by Melbourne Robotic Lab. to visit Harvard BioRobotics Lab

Related Publications

 A. Mohammadi, J. Lavranos, R. D. Howe, P. Choong and D. Oetomo

  Flexo-glove: A 3D Printed Soft Exoskeleton Robotic Glove for Impaired Hand Rehabilitation and Assistance

  40th International Engineering in Medicine and Biology Conference (EMBC), 2018.

Full Text  PDF 

via Project3 – Flexo-glove

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[Abstract] Mobile Game-based Virtual Reality Program for Upper Extremity Stroke Rehabilitation

Abstract

Stroke rehabilitation requires repetitive, intensive, goal-oriented therapy. Virtual reality (VR) has the potential to satisfy these requirements. Game-based therapy can promote patients’ engagement in rehabilitation therapy as a more interesting and a motivating tool. Mobile devices such as smartphones and tablet PCs can provide personalized home-based therapy with interactive communication between patients and clinicians. In this study, a mobile VR upper extremity rehabilitation program using game applications was developed. The findings from the study show that the mobile game-based VR program effectively promotes upper extremity recovery in patients with stroke. In addition, patients completed two weeks of treatment using the program without adverse effects and were generally satisfied with the program. This mobile game-based VR upper extremity rehabilitation program can substitute for some parts of the conventional therapy that are delivered one-on-one by an occupational therapist. This time-efficient, easy to implement, and clinically effective program would be a good candidate tool for tele-rehabilitation for upper extremity recovery in patients with stroke. Patients and therapists can collaborate remotely through these e-health rehabilitation programs while reducing economic and social costs.

 

via Mobile Game-based Virtual Reality Program for Upper Extremity Stroke Rehabilitation. – PubMed – NCBI

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[Abstract] Evolution of upper limb kinematics four years after subacute robot-assisted rehabilitation in stroke patients

Purpose: To assess functional status and robot-based kinematic measures four years after subacute robot-assisted rehabilitation in hemiparesis.

Material and methods: Twenty-two patients with stroke-induced hemiparesis participated in a ≥3-month upper limb combined program of robot-assisted and occupational therapy from two months post-stroke, and received community-based therapy after discharge. Four years later, nineteen (86%) participated in this long-term follow-up study. Assessments two, five and 54 months post-stroke included Fugl-Meyer (FM), Modified Frenchay Scale (MFS, at Month 54) and robot-based kinematic measures of targeting tasks in three directions, north, paretic and non-paretic: distance covered, velocity, accuracy (RMS error from straight line) and smoothness (number of velocity peaks; upward changes in accuracy and smoothness measures represent worsening). Analysis was stratified by FM score at two months: ≥17 (Group 1) or < 17 (Group 2). Correlation between impairment (FM) and function (MFS) was explored at 54 months.

Results: Fugl-Meyer scores were stable from five to 54 months (+1[-2;4], median[1st;3rd quartiles], ns). Kinematic changes in the three directions pooled were: distance covered, -1[-17;2]% (ns); velocity, -8[-32;28]% (ns); accuracy, +6[-13;98]% (ns); smoothness, +44[-6;126]% (p<0.05). Group 2 showed decline vs Group 1 (p<0.001) in FM (Group 1, +3[1;5], p<0.01; Group 2, -7[-11;-1], ns) and accuracy (Group 1, -3[-27;38]%, ns; Group 2, +29[17;140]%, p<0.001). At 54 months, FM and MFS were highly correlated (Pearson’s rho = 0.89; p<0.001).

Conclusions: While impairment appeared stable four years after robot-assisted upper limb training during subacute post-stroke phase, kinematic performance deteriorated in spite of community-based therapy, especially in patients with more severe impairment.

 

via Evolution of upper limb kinematics four years after subacute robot-assisted rehabilitation in stroke patients: International Journal of Neuroscience: Vol 0, No ja

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