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Energy-Efficient Posture Classification with Filtered Sensed Data from A Single 3-Axis Accelerometer Deployed in WSN
unpublished
Wireless Sensor Networks (WSNs) provide rich and detailed measurements of the physical phenomenon that they monitor. With the sensed data, a variety of pervasive applications can be developed. One category of those applications are classifications based on supervised machine learning, with one example being postures recognition with data from body sensor networks (BSNs). Conventionally for accuracy reason, raw data from the BSN sensors, such as accelerometers or other inertial devices, is
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