scholarly journals Customizing Robot-Assisted Passive Neurorehabilitation Exercise Based on Teaching Training Mechanism

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yingnan Lin ◽  
Qingming Qu ◽  
Yifang Lin ◽  
Jieying He ◽  
Qi Zhang ◽  
...  
Keyword(s):  
Upper Extremity ◽  
Control Strategy ◽  
Early Stage ◽  
Passive Movement ◽  
Interactive System ◽  
Stroke Survivors ◽  
Robot Assisted ◽  
Patient Centeredness ◽  
Training Trajectory ◽  
Clinical Experiments

Passive movement is an important mean of rehabilitation for stroke survivors in the early stage or with greater paralysis. The upper extremity robot is required to assist therapists with passive movement during clinical rehabilitation, while customizing is one of the crucial issues for robot-assisted upper extremity training, which fits the patient-centeredness. Robot-assisted teaching training could address the need well. However, the existing control strategies of teaching training are usually commanded by position merely, having trouble to achieve the efficacy of treatment by therapists. And deficiency of flexibility and compliance comes to the training trajectory. This research presents a novel motion control strategy for customized robot-assisted passive neurorehabilitation. The teaching training mechanism is developed to coordinate the movement of the shoulder and elbow, ensuring the training trajectory correspondence with human kinematics. Furthermore, the motion trajectory is adjusted by arm strength to realize dexterity and flexibility. Meanwhile, the torque sensor employed in the human-robot interactive system identifies movement intention of human. The goal-directed games and feedbacks promote the motor positivity of stroke survivors. In addition, functional experiments and clinical experiments are investigated with a healthy adult and five recruited stroke survivors, respectively. The experimental results present that the suggested control strategy not only serves with safety training but also presents rehabilitation efficacy.

Poster 99 Robot-Assisted Distal Upper Extremity Repetitive Task Practice in Chronic Stroke Survivors

2011 ◽  
Vol 92 (10) ◽  
pp. 1720
Author(s):  
James Lynskey ◽  
Pamela Bosch ◽  
Kay Wing ◽  
Jennifer Janowicz ◽  
Jennifer Kramer ◽  
...  
Keyword(s):  
Upper Extremity ◽  
Chronic Stroke ◽  
Stroke Survivors ◽  
Robot Assisted ◽  
Task Practice

scholarly journals Is robot-assisted therapy effective in upper extremity recovery in early stage stroke? —a systematic literature review

2017 ◽  
Vol 29 (6) ◽  
pp. 1108-1112 ◽  
Author(s):  
GaYeong Kim ◽  
SeungYeop Lim ◽  
HyunJong Kim ◽  
ByungJoon Lee ◽  
SeungChul Seo ◽  
...  
Keyword(s):  
Literature Review ◽  
Upper Extremity ◽  
Systematic Literature Review ◽  
Early Stage ◽  
Robot Assisted

scholarly journals EEG Fractal Analysis Reflects Brain Impairment after Stroke

Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 592
Author(s):  
Maria Rubega ◽  
Emanuela Formaggio ◽  
Franco Molteni ◽  
Eleonora Guanziroli ◽  
Roberto Di Marco ◽  
...  
Keyword(s):  
Early Stage ◽  
Brain Activity ◽  
Phase 1 ◽  
Behavioral Changes ◽  
Stroke Survivors ◽  
Eeg Signals ◽  
Novel Treatments ◽  
Fractal Measures ◽  
Underlying Mechanisms ◽  
Random Fluctuations

Stroke is the commonest cause of disability. Novel treatments require an improved understanding of the underlying mechanisms of recovery. Fractal approaches have demonstrated that a single metric can describe the complexity of seemingly random fluctuations of physiological signals. We hypothesize that fractal algorithms applied to electroencephalographic (EEG) signals may track brain impairment after stroke. Sixteen stroke survivors were studied in the hyperacute (<48 h) and in the acute phase (∼1 week after stroke), and 35 stroke survivors during the early subacute phase (from 8 days to 32 days and after ∼2 months after stroke): We compared resting-state EEG fractal changes using fractal measures (i.e., Higuchi Index, Tortuosity) with 11 healthy controls. Both Higuchi index and Tortuosity values were significantly lower after a stroke throughout the acute and early subacute stage compared to healthy subjects, reflecting a brain activity which is significantly less complex. These indices may be promising metrics to track behavioral changes in the very early stage after stroke. Our findings might contribute to the neurorehabilitation quest in identifying reliable biomarkers for a better tailoring of rehabilitation pathways.

scholarly journals Alterations in Muscle Networks in the Upper Extremity of Chronic Stroke Survivors

2021 ◽  
pp. 1-1
Author(s):  
Michael Houston ◽  
Xiaoyan Li ◽  
Ping Zhou ◽  
Sheng Lia ◽  
Jinsook Roh ◽  
...  
Keyword(s):  
Upper Extremity ◽  
Chronic Stroke ◽  
Stroke Survivors

Robot-assisted therapy for upper extremity rehabilitation in Erb-Duchenne palsy: A case report

2020 ◽  
Vol 81 ◽  
pp. 8
Author(s):  
I. Akgün ◽  
E.E. Avcı ◽  
E. Timurtaş ◽  
İ. Demirbüken ◽  
M.G. Polat
Keyword(s):  
Case Report ◽  
Upper Extremity ◽  
Robot Assisted ◽  
Upper Extremity Rehabilitation

scholarly journals The extent of altered digit force direction correlates with clinical upper extremity impairment in chronic stroke survivors

2015 ◽  
Vol 48 (2) ◽  
pp. 383-387 ◽  
Author(s):  
Na Jin Seo ◽  
Leah R. Enders ◽  
Binal Motawar ◽  
Marcella L. Kosmopoulos ◽  
Mojtaba Fathi-Firoozabad
Keyword(s):  
Upper Extremity ◽  
Chronic Stroke ◽  
Stroke Survivors ◽  
Force Direction ◽  
Upper Extremity Impairment

scholarly journals Investigating the feasibility and acceptability of real-time visual feedback in reducing compensatory motions during self-administered stroke rehabilitation exercises: A pilot study with chronic stroke survivors

2019 ◽  
Vol 6 ◽  
pp. 205566831983163 ◽  
Author(s):  
Shayne Lin ◽  
Jotvarinder Mann ◽  
Avril Mansfield ◽  
Rosalie H Wang ◽  
Jocelyn E Harris ◽  
...  
Keyword(s):  
Pilot Study ◽  
Upper Extremity ◽  
Visual Feedback ◽  
Feedback System ◽  
Optimal Recovery ◽  
Chronic Stroke ◽  
Stroke Survivors ◽  
Perfect Agreement ◽  
Rehabilitation Programs ◽  
Shoulder Elevation

Introduction Homework-based rehabilitation programs can help stroke survivors restore upper extremity function. However, compensatory motions can develop without therapist supervision, leading to sub-optimal recovery. We developed a visual feedback system using a live video feed or an avatar reflecting users' movements so users are aware of compensations. This pilot study aimed to evaluate validity (how well the avatar characterizes different types of compensations) and acceptability of the system. Methods Ten participants with chronic stroke performed upper-extremity exercises under three feedback conditions: none, video, and avatar. Validity was evaluated by comparing agreement on compensations annotated using video and avatar images. A usability survey was administered to participants after the experiment to obtain information on acceptability. Results There was substantial agreement between video and avatar images for shoulder elevation and hip extension (Cohen's κ: 0.6–0.8) and almost perfect agreement for trunk rotation and flexion (κ: 0.80–1). Acceptability was low due to lack of corrective prompts and occasional noise with the avatar display. Most participants suggested that an automatic compensation detection feature with visual and auditory cuing would improve the system. Conclusion The avatar characterized four types of compensations well. Future work will involve increasing sensitivity for shoulder elevation and implementing a method to detect compensations.

scholarly journals Action Observation Treatment-Based Exoskeleton (AOT-EXO) for Upper Extremity After Stroke: Study Protocol for a Randomised Controlled Trial

2021 ◽  
Author(s):  
Zejian Chen ◽  
Nan Xia ◽  
Chang He ◽  
Minghui Gu ◽  
Jiang Xu ◽  
...  
Keyword(s):  
Upper Extremity ◽  
Functional Disability ◽  
Motor Evoked Potentials ◽  
Action Observation ◽  
Controlled Trial ◽  
Measurement Unit ◽  
Motor Deficit ◽  
Robot Assisted ◽  
Clinical Trial Registry ◽  
Resting Motor Threshold

Abstract Background Stroke produces multiple symptoms, including sensory, motor, cognitive and psychological dysfunctions, among which motor deficit is the most common and is widely recognized as a major contributor to long-term functional disability. Robot-assisted training is effective in promoting upper extremity muscle strength and motor impairment recovery after stroke. Additionally, action observation treatment can enhance the effects of physical and occupational therapy by increasing neural activation. The AOT-EXO trial aims to investigate whether action observation treatment coupled with robot-assisted training could enhance motor circuit activation and improve upper extremity motor outcomes. Methods The AOT-EXO trial is a multicentre, prospective, three-group randomized controlled trial (RCT). We will screen and enrol 132 eligible patients in the trial implemented in the Department of Rehabilitation Medicine of Tongji Hospital, Optical Valley Branch of Tongji Hospital and Hubei Province Hospital of Integrated Chinese & Western Medicine in Wuhan, China. Prior to study participation, written informed consent will be obtained from eligible patients in accordance with the Declaration of Helsinki. The enrolled stroke patients will be randomised to three groups: the CT group (conventional therapy); EXO group (exoskeleton therapy) and AOT-EXO group (action observation treatment-based exoskeleton therapy). The patients will undergo blinded assessments at baseline, post-intervention (after 4 weeks) and follow-up (after 12 weeks). The primary outcome will be the Fugl-Meyer Assessment for Upper Extremity (FMA-UE). Secondary outcomes will include the Action Research Arm Test (ARAT), modified Barthel Index (MBI), kinematic metrics assessed by inertial measurement unit (IMU), resting motor threshold (rMT), motor evoked potentials (MEP), functional magnetic resonance imaging (fMRI) and safety outcomes. Discussion This trial will provide evidence regarding the feasibility and efficacy of the action observation treatment-based exoskeleton (AOT-EXO) for post-stroke upper extremity rehabilitation and elucidate the potential underlying kinematic and neurological mechanisms. Trial Registration: Chinese Clinical Trial Registry identifier: ChiCTR1900026656. Registered on 17 October 2019.

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