This paper describes a method of detecting and analyzing breathing rate and approximate depth during physical activity in a Bluetooth Wireless On-Body-Network (OBN) in the context of a Spinal Cord Injured patient. Conventional signal processing techniques and sensor fusion through a Linear Kalman Filter will be used to fuse signals from a piezoelectric breathing band and two tri-axis accelerometers. Results will show that the proposed method provides very accurate measurements of breathing rate and depth at rest and during physical activity.

Pedometers are known to have steps estimation issues. This is mainly attributed to their innate acceleration based measuring sensory. A micro-machined gyroscope (better immunity to acceleration) based pedometer is proposed. Through syntactic data recognition of apriori knowledge of human shank's dynamics and temporally précised detection of heel strikes permitted by Wavelet decomposition, an accurate and robust pedometer is acquired.

This paper describes a novel ambulatory multiparameter physiological monitoring system. The ambulatory monitoring system forms a body area network (BAN) and acquires stress related physiological parameters in realtime. The system has been tested in the laboratory and emotional changes have been effectively detected.

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