• Proceedings of the Korea Information Processing Society Conference
• /
• 2017.04a
• /
• pp.1163-1165
• /
• 2017

헬스케어와 IT가 결합한 융합산업이 발전하면서 웨어러블 디바이스와 스마트폰을 연계하여 운동정보를 제공하는 제품이 증가하고 있다. 특히 손목에 착용하는 스마트밴드를 통해 생체신호 및 움직임을 감지하고 신체상태 및 활동량을 제공하고 있다. 그러나 단순한 운동 동작의 횟수나 시간만을 알려주는 서비스를 제공하고 있어 정확한 운동 및 건강의 관리가 힘들다. 이에 본 논문에서는 사용자에게 운동의 정확성 여부를 알려주고 건강 및 운동에 대한 통계 정보를 제공하는 클라우드 서비스 기반의 운동 정보 제공 시스템을 제안한다. 제안 시스템은 스마트밴드와 모션 디바이스를 통해 모션 및 심박데이터를 취득하여 스마트폰을 통해 실시간으로 운동의 정확도 여부 및 활동 정보를 제공한다. 또한 클라우드 플랫폼의 서비스 가상 머신을 통해 세밀한 운동 자세 및 운동량, 신체 상태 통계 등의 피드백 서비스를 제공한다.

• Journal of rehabilitation welfare engineering & assistive technology
• /
• v.7 no.2
• /
• pp.47-54
• /
• 2013

In this paper, we present an inertial sensor-based motion capturing system to measure and analyze whole body movements. This system implements a wireless AHRS(attitude heading reference system) we developed using a combination of rate gyroscope, accelerometer and magnetometer sensor signals. Several AHRS modules mounted on segments of the patient's body provide the quaternions representing the patient segments's orientation in space. We performed 3D motion capture using the quaternion data calculated. And a method is also proposed for calculating three-dimensional inter-segment joint angle which is an important bio-mechanical measure for a variety of applications related to rehabilitation. To evaluate the performance of our AHRS module, the Vicon motion capture system, which offers millimeter resolution of 3D spatial displacements and orientations, is used as a reference. The evaluation resulted in a RMSE of 2.56 degree. The results suggest that our system will provide an in-depth insight into the effectiveness, appropriate level of care, and feedback of the rehabilitation process by performing real-time limbs or gait analysis during the post-stroke recovery process.

• Journal of rehabilitation welfare engineering & assistive technology
• /
• v.9 no.2
• /
• pp.137-144
• /
• 2015

In this paper, we present an inertial sensor-based gait analysis system to measure and analyze lower-limb movements. We developed an integral AHRS(Attitude Heading Reference System) using a combination of rate gyroscope, accelerometer and magnetometer sensor signals. Several AHRS modules mounted on segments of the patient's body provide the quaternions representing the patient segments's orientation in space. And a method is also proposed for calculating three-dimensional inter-segment joint angle which is an important bio-mechanical measure for a variety of applications related to rehabilitation. To evaluate the performance of our AHRS module, the Vicon motion capture system, which offers millimeter resolution of 3D spatial displacements and orientations, is used as a reference. The evaluation resulted in a RMSE(Root Mean Square Error) of 1.08 and 1.72 degree in yaw and pitch angle. In order to evaluate the performance of our the gait analysis system, we compared the joint angle for the hip, knee and ankle with those provided by Vicon system. The result shows that our system will provide an in-depth insight into the effectiveness, appropriate level of care, and feedback of the rehabilitation process by performing real-time limb or gait analysis during the post-stroke recovery.