Dedicated Computational Microsystems for Biomedical Sensors

"Human activity monitoring with a wrist worn instrument, the actigraph, hassuccessfully been used to quantify bulk human activity, and predict macro-quantitiessuch as hr:min of sleep. These devices do not yield information about the underlyingmovement physiology because the simple detection methods ignore important signalcharacteristics. Recently it was demonstrated heart and lung ballistic activityare measurable from the wrist with a wireless device the size of a wristwatch.These conclusions derived from extensive bench top data processing and sophisticatedtools like the wavelet transform. This SBIR seeks to build the next generationactigraph, one that can predict heart rate and breath rate from a sleeping orambulatory individual "in situ", and expand this technique to other physiologicalprocesses. The device will use a custom built analog integrated circuit (from arelated SBIR), coprocessor, adaptive digital filtering and 'non-stationary spectrum'processing techniques. Phase I will concentrate on building the Digital SignalProcessing (DSP) actigraph, and testing it worn on sleeping subjects. One goal ofthe DSP actigraph is produce a stream of estimates for heart and breath rate overthe duration of a sleep period. Phase II will extend the technique to ambulatorysubjects, and improve hardware producibility. The ambulatory wrist worn DSP actigraph will able to measure ballistic cardiac andbreath rates "in situ" in near real time,