Abstract: The present disclosure provides a bracewear for spinal correction and a system for posture training. The system for posture training involves both active and passive corrective forces by using the bracewear and a biofeedback system to address the spinal correction, which can eliminate the adversity of conventional hard braces and reduce the psychological and physiological barriers to treatment.

Abstract: The present disclosure provides a bracewear for spinal correction and a system for posture training. The system for posture training involves both active and passive corrective forces by using the bracewear and a biofeedback system to address the spinal correction, which can eliminate the adversity of conventional hard braces and reduce the psychological and physiological barriers to treatment.

Abstract: A biofeedback system for monitoring patient-related signals of a patient having adolescent idiopathic scoliosis (AIS) is disclosed. The present invention provides a personalized biofeedback to the patient based on the patient-related signals for restoring balance in muscle activities and reducing displacement of both sides of the patient's spine as a treatment for AIS. The biofeedback system comprises clothing integrated with posture monitoring sensors, and one or more computational systems comprising a sensor-based sEMG posture training subsystem for providing posture training and a posture monitoring subsystem for providing progressive training through daily activities. The sensor-based sEMG posture training subsystem comprises a posture training device coupled to a plurality of sEMG sensors, a feedback device and a calibration system.

Abstract: A biofeedback system for monitoring patient-related signals of a patient having adolescent idiopathic scoliosis (AIS) is disclosed. The present invention provides a personalized biofeedback to the patient based on the patient-related signals for restoring balance in muscle activities and reducing displacement of both sides of the patient's spine as a treatment for AIS. The biofeedback system comprises clothing integrated with posture monitoring sensors, and one or more computational systems comprising a sensor-based sEMG posture training subsystem for providing posture training and a posture monitoring subsystem for providing progressive training through daily activities. The sensor-based sEMG posture training subsystem comprises a posture training device coupled to a plurality of sEMG sensors, a feedback device and a calibration system.

Abstract: A garment, in a form of tank top, for monitoring patient-related signals of a patient having scoliosis and thereby enabling the patient to obtain a personalized biofeedback is provided. The garment are integrated with plural sensors, a sensor interface and a smart control unit (SCU), allowing the patient-related signals to be non-intrusively measured by the sensors while maintaining comfort to the patient when the patient wears the garment. The SCU is communicable with the sensors via the sensor interface and aggregates the patient-related signals. A computing server outside the garment receives the aggregated patient-related signals from the SCU via a user access device such as a smartphone, and processes the aggregated patient-related signals to generate the personalized biofeedback, which is then forwarded to the user access device for presentation to the patient. Machine learning algorithms are used to process the patient-related signals in generating the biofeedback.