Technical Name Brain-Computer Interface Modulated Reality Extremity Coordination Rehabilitation Exoskeletal System
Project Operator Kaohsiung Medical University
Project Host 陳嘉炘
Summary
The rehabilitation exoskeleton system provides pelvic control, provides training safety,is equipped with a dynamic weight support system, which provides immediate dynamic weight support follow changes in center of gravity, increasing the diversity of application fields. Combined with encephalogram monitoringaugmented reality, it provides visual feedback during rehabilitation, as well as real-time assessment of brain activationattention during training. The wireless encephalogram device has a low-power transmissionhigh-resolution miniaturized circuit design, which is easy to wearuse,does not affect long-term rehabilitation training.
Scientific Breakthrough
1. The dynamic weight support system effectively controls weight support error within 4N, which is better than other systems provided
 
 2. The exoskeleton system controls accuracy within 0.2 degree when encounter abrupt joint movement, which provides the system high accuracy of movement controlsafety during training
 
 3. Integration of electroencephalography signalsalgorithm, which provides the system dynamic signal feedbackattention tracking of the user
Industrial Applicability
This system combines weight support exoskeleton, visual feedback reality interactive softwarewireless electroencephalogram detection in rehabilitation training. Scientific evidence supports its high-efficiency, safereal-time feedback as rehabilitation training device. It can provide rehabilitation training for those with extremities weakness with intelligent assistance, dynamic weight support, real-time monitoring training system,potential use in a variety of fields, such as medical facilities for clinical rehabilitation training,long-term care system for community rehabilitation training with improved quality.
Keyword weight support exoskeleton visual feedback reality interactive software wireless electroencephalogram novel rehabilitation
Notes
  • Contact
  • Chia-Hsin Chen
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