In this paper a novel portable posture monitoring and feedback system is proposed. System is designed to be unobtrusively used during daily activities and provide alternative solution to traditional bracing used in treatment of scoliosis. System consists of wearable sensor network for posture data acquisition, wireless data transmission and conventional smartphone for data processing, visualization and vibrating feedback generation. Special data acquisition board is designed for data sampling from sensor network and wireless transmission to smartphone. A custom made Android application is used for real time data processing, current posture model visualization, data logging and instantaneous feedback. System was tested for posture monitoring and feedback generation on multiple test subjects. Tests demonstrated systems effectiveness on improving posture related behavior and ability to help subject to hold specific reference posture performing similar task as traditional bracing.
We propose a hybrid architecture of wired and wireless sensors for smart fabric with applications including body dynamics and shape monitoring and patient rehabilitation. Our system is capable of acquiring data from up to 200 onbody sensors with 50Hz sampling rate using conventional low-cost hardware. The sensing and data processing is done in real time and the results available on a smaptphone, tablet or pc in 3D visual form or as alerts. The user experience of the demo will include trying out smart clothing that is enabled with the shape sensing fabric and observing the body shape dynamics on-screen in real time.
In this paper a method for efficient data acquisition from sensor network with large number of nodes is proposed. A specific design allows simple device connection in daisy-chain configuration, thus removing addressing problems and allowing synchronized sampling design using just 4 wires. Several limitations are considered to provide mathematical model for estimation of maximum number of sensor nodes. An experimental setup was designed which demonstrated theoretical ability to acquire data from up to 200 sensors with 50 Hz sampling rate using conventional low-cost hardware, however, more advanced setup could allow to increase maximum number of sensors several times. The wiring structure of the network as well as hardware is specifically designed for use in smart garments or similar applications that require sensor integration in compact environment and low-power, real-time performance.
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