Development of computer-based environment for simulating the voluntary upper-limb movements of persons with disability

Speed-Interactive Pedaling Training Using Smartphone Virtual Reality Application for Stroke Patients: Single-Blinded, Randomized Clinical Trial

This study aimed to investigate the effects of speed-interactive pedaling training (SIPT) using a smartphone virtual reality application to improve lower limb motor function, trunk sitting balance, and gait in stroke patients. Forty-two patients who had previously experienced a stroke and could sit independently participated in the study. The subjects were assigned to the SIPT group (n = 21) and the control group (n = 21). The SIPT group had cycle training with SIPT for 40 min a day, five days a week, in a six-week period, in addition to conventional therapy. The control group had cycle training without SIPT and conventional therapy. The Fugl–Meyer Assessment, postural sway, modified functional reach test, trunk impairment scale, and spatiotemporal parameters of gait were used to assess the changes in lower extremity function, the static balance of sitting, the dynamic balance of sitting, and gait ability after the intervention. The Fugl–Meyer Assessment, postural sway, modified functional reach test, trunk impairment scale, and gait ability in the SIPT group were significantly better compared to that of the control group (p < 0.05). Based on this result, we propose that SIPT, which improves function, balance, and gait, could be used as an effective training method to improve patients’ functional activities in the clinical setting. The results of this study suggest that SIPT could be used as an effective training method to restore a patient’s function by improving trunk balance and motor function.

Effects of robot-assisted therapy on upper extremity function and activities of daily living in hemiplegic patients: A single-blinded, randomized, controlled trial

BACKGROUND

Many robots can induce passive movements and passive resistance movements to facilitate recovery of upper-extremity function, but it is rare to find robots that can also enable active resistance movements.

OBJECTIVE

The purpose of this study was to investigate the effects of robot-assisted therapy on upper-extremity function and the ability to perform activities of daily living (ADL) in patients with stroke-induced hemiplegia.

METHODS

Thirty patients with stroke-induced hemiplegia were randomly assigned to the experimental and control groups, with 15 patients in each group. All subjects underwent general occupational therapy consisting of five 30-min sessions per week for 8 weeks, in addition to 30 min of robot-assisted therapy for the experimental group and 30 additional min of general occupational therapy for the control group for each session.

RESULTS

Both the experimental and control groups showed a statistically significant increase in post-treatment Fugl-Meyer assessment and modified Barthel index scores compared to the pre-treatment scores. Intergroup comparisons revealed that the experimental group showed a statistically significant greater increase in scores for all assessments than the control group did (p< 0.05).

CONCLUSION

The findings from this study showed that combining robot-assisted therapy with general occupational therapy may enhance upper-extremity function and the ability to perform ADL in patients with stroke-induced hemiplegia compared to those obtained with general occupational therapy alone.

Command control for functional electrical stimulation hand grasp systems using miniature accelerometers and gyroscopes

Recent commercially available miniature sensors have the potential to improve the functions of functional electrical stimulation (FES) systems in terms of control, reliability and robustness. A new control approach using a miniature gyroscope and an accelerometer was studied. These sensors were used to detect the linear acceleration and angular velocity of residual voluntary movements on upper limbs and were small and easy to put on. Five healthy subjects and three cervical spinal cord injured subjects were recruited to evaluate this controller. Sensors were placed on four locations: the shoulder, upper arm, wrist and hand. A quick forward-and-backward movement was employed to produce a distinctive waveform that was different from general movements. A detection algorithm was developed to generate a command signal by identifying this distinctive waveform through the detection of peaks and valleys in the sensor's signals. This command signal was used to control different FES hand grasp patterns. With a specificity of 0.9, the sensors had a success rate of 85-100% on healthy subjects and 82-97% on spinal cord injured subjects. In terms of sensor placement, the gyroscope was better as a control source than the accelerometer for wrist and hand positions, but the reverse was true for the shoulder.