A wrist watch based system, which can measure electrocardiogram (ECG) and photoplethysmogram (PPG), is presented in this work. By using both ECG and PPG we also measure pulse transit time (PTT), which studies show to correlate well with blood pressure (BP). The system is also capable of monitoring heart rate using either ECG or PPG and can monitor blood oxygenation by easily replacing the PPG sensors with a different set. In this work, we investigate methods to train a fitting function to convert a PTT measurement to its corresponding systolic BP. We also validate measurements on different postures and show the value of calibrating the device for each posture. This system, called BioWatch, can potentially facilitate continuous and ubiquitous monitoring of ECG, PPG, heart rate, blood oxygenation and BP.

In this paper, we present a framework to analyze the propagation of measurement errors through the body composition equations. This is done through the equations for body composition assessment (BCA), for single/multifrequency (SF, MF) body impedance analysis (BIA) approaches. We show that it is possible to estimate a priori the error variance on the BCA parameters from the error measurement in the weight, height, and impedance. The theoretical results are validated through the simulation and experimental data coming from the low-cost AFE4300 impedance spectrometer developed by Texas Instruments. This new spectrometer has been calibrated and characterized by performing measurements on phantoms and foot-to-foot body impedance measurements. The influence of the number of measurement frequencies on the accuracy of BCA is also studied for MF-BIA approach. Ultimately, the measurement error framework can be used to evaluate the suitability of an impedance system for BIA.Index Terms-AFE4300, body impedance analysis (BIA), electrical bioimpedance (EBI), electrical impedance spectroscopy (EIS), error propagation theory, measurement uncertainties.

Advancements are being made towards a cheap and effective means for health monitoring. A mobile monitoring system is proposed for monitoring a bicycle rider using light weight, low power wireless sensors. Biometric and environmental information pertaining to the bicycle rider is captured, transmitted to, and stored in a remote database with little user interaction required. Remote users have real time access to the captured information through a web application. Possible applications for this system include the monitoring of a soldier in the battlefield and the monitoring of a patient during an ambulance ride.

The advancement in technology for patient monitoring and smart living environments is making a huge impact on providing health care for the elderly and needy population. An energy efficient context aware system for sensing and reporting events based on wireless sensor networks (WSN) is presented in this paper. It is demonstrated that it is possible to build and deploy power efficient systems with an extended battery life by exploiting the recent technological innovations and properly using the architectural framework for supporting WSNs. The system evolves with highly localized computations aided by the contextual information which helps in detecting events and alerting the care provider for only the positive events.

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