Heart rate estimation from FBG sensors using cepstrum analysis and sensor fusion.

This paper presents a method of estimating heart rate from arrays of fiber Bragg grating (FBG) sensors embedded in a mat. A cepstral domain signal analysis technique is proposed to characterize Ballistocardiogram (BCG) signals. With this technique, the average heart beat intervals can be estimated by detecting the dominant peaks in the cepstrum, and the signals of multiple sensors can be fused together to obtain higher signal to noise ratio than each individual sensor.

Processing of wearable sensor data on the cloud - a step towards scaling of continuous monitoring of health and well-being.

As part of a sleep monitoring project, we used actigraphy based on body-worn accelerometer sensors to remotely monitor and study the sleep-wake cycle of elderly staying at nursing homes. We have conducted a fifteen patient trial of a sleep activity pattern monitoring (SAPM) system at a local nursing home. The data was collected and stored in our server and the processing of the data was done offline after sleep diaries used for validation and ground truth were updated into the system.

Evaluation and analysis of multimodal sensors for developing in and around the bed patient monitoring system.

Due to the decline in physical and cognitive abilities, many frail elderly may have to lie in the bed most of their time. It is not feasible to monitor them continuously through manual observations alone. This issue can be resolved by embedding a set of multimodal sensors into the bed and providing automated activity recognition intelligence.