Posts Tagged Medical treatment
[Abstract] Technical validation of an integrated robotic hand rehabilitation device: Finger independent movement, EMG control, and EEG-based biofeedback
[Abstract] Exerciser for rehabilitation of the Arm (ERA): Development and unique features of a 3D end-effector robot
[Abstract] Detecting voluntary gait intention of chronic stroke patients towards top-down gait rehabilitation using EEG
[Abstract] Benefits of using a voice and EMG-driven actuated glove to support occupational therapy for stroke survivors.
Many mechatronic devices exist to facilitate hand rehabilitation, however few directly address deficits in muscle activation patterns while also enabling functional task practice.
We developed an innovative voice and electromyography-driven actuated (VAEDA) glove, which is sufficiently flexible/portable for incorporation into hand-focused therapy post-stroke. The therapeutic benefits of this device were examined in a longitudinal intervention study. Twenty-two participants with chronic, moderate hand impairment (Chedoke-McMaster Stroke Assessment Stage of Hand (CMSA-H=4)) enrolled >8 months post-stroke for 18 one-hour training sessions (3x/week) employing a novel hand-focused occupational therapy paradigm, either with (VAEDA) or without (No-VAEDA) actuated assistance.
Outcome measures included CMSA-H, Wolf Motor Function Test (WMFT), Action Research Arm Test, Fugl-Meyer Upper Extremity Motor Assessment (FMUE), grip and pinch strength and hand kinematics. All outcomes were recorded at baseline and endpoint (immediately after and 4 weeks post-training).
Significant improvement was observed following training for some measures for the VAEDA group (n=11) but for none of the measures for the No-VAEDA group (n=11). Specifically, statistically significant gains were observed for CMSA-H (p=0.038) and WMFT (p=0.012) as well as maximum digit aperture subset (p=0.003, n=7), but not for the FMUE or grip or pinch strengths.
In conclusion, therapy effectiveness appeared to be increased by employment of the VAEDA glove, which directly targets deficits in muscle activation patterns.
21-23 Oct. 2015
In the last two decades, robot-aided rehabilitation has become widespread, particularly for upper limb movement rehabilitation. In this Doctoral Consortium I present a system for physical and cognitive rehabilitation that uses a combination of Serious Games to allow the monitoring and progress tracking of a person during physical therapy. The system records physical and cognitive states through the interaction with the advance robotic arm in order to assess the users hand-eye coordination, response interaction, working memory and concentration rates.
Virtual reality therapy systems have the potential to increase the intensity and frequency of physical activity of stroke patients at home. This might help to increase the dose of rehabilitation, without the costs associated with clinic visits and therapist supervision.
We present a therapy game that continuously estimates the patient’s arm reachable three-dimensional (3D) workspace with a voxel-based model and selects targets to be reached accordingly, in order to increase challenge without causing frustration. This exercise is implemented on a novel, inertial measurement unit (IMU) based virtual reality system for the training of upper limb function. We present data from a pilot trial with 5 chronic stroke patients who trained for 6 weeks at home and without therapist supervision.
On average, the patients’ in-game assessed 3D workspace grew by 10.7% in volume and their score on the Fugl-Meyer Upper Extremity score improved by 5 points. The average self-selected therapy time, over the course of the therapy, was 16.8 h. These results suggest that the proposed assessment-driven target selection is viable for unsupervised home therapy and could form the basis for additional therapy games in the future.
[ARTICLE] Encouraging specific intervention motions via a robotic system for rehabilitation of hand function
A knowledge gap exists for how to improve hand rehabilitation after stroke using robotic rehabilitation methods, and non-robotic hand rehabilitation methods show only small patient improvements. A proposed solution for this knowledge gap is to integrate the strengths of three of the most favorable rehabilitation strategies for post-stroke rehabilitation of hand function, which are constraint-induced movement therapy (CIMT), high-intensity therapy, and repetitive task training, with a robotic rehabilitation gaming system.
To create a system that is composed of collaborative therapy efforts, we must first understand how to encourage rehabilitation intervention motions. An experiment was conducted in which healthy participants were asked to complete six levels of a rehabilitation game, each level designed to encourage a specific therapeutic intervention, and a control, where participants were asked to complete undefined exercise motions.
The results showed that participants’ motions were significantly different than the control while playing each of the levels. Upon comparing the actual paths of participants to the paths encouraged by the levels, it was discovered that the participants followed the intended path while encouragement was being provided for them to do so. When the encouraged motions required quick, hard motions, the participants would follow an aliased version of the intended path.
This study suggests that robotic rehabilitation systems can not only change how a participant moves, but also encourage specific motions designed to mimic therapeutic interventions.