SBIR-STTR Award

ZIN Technologies in collaboration with the Cleveland Clinic Foundation will use their combined experience and research and development expertise to develop a new compact ambulatory biometric data system for space and commercial terrestrial use. This design will improve on the existing design onboard the International Space Station and other available systems by increasing the system resolution from 12 to 24 bits, reducing the weight by 40%, decreasing the overall volume by 70%, increasing usability, extending the dynamic range of biological signals that can be recorded, increasing on-board memory capacity, and providing additional instantaneous feedback to users through an extended local processing capability. Data will be acquired through a cell phone sized unit possibly attached to a subjects belt loop. Data is transmitted wirelessly to a PDA (Personal Digital Assistant) where it can be accessed and viewed by the subject. Data will also be wirelessly transmitted to a processing unit for real-time transmission to ground. When out of range of the processing unit, data will be stored onboard the monitoring device for later transmission. The design will allow for real time data streaming to ground stations and easy accessible viewing of metrics by astronauts on-orbit (or medical subjects terrestrially).

BioWATCH is a modular ambulatory compact wireless biomedical data acquisition system. More specifically, it is a data acquisition unit for acquiring signals from biomedical sensors using modular acquisition modules attached to a common data and power bus. Several module slots allow the user to configure the unit by inserting sensor specific modules. The data is then sent real time from the unit over any commercially implemented wireless network including 802.11b/g, WCDMA, GSM, or EDGE. BioWATCH is of a distributed computing hierarchy and has a common data controller on each sensor module. This innovation allows for the modularity of the device along with the tailored ability to control the cards using a relatively small master processor. The distributed nature of this system affords the modularity, size, and power consumption that betters the current state-of-the-art in medical ambulatory data acquisition. The current state-of-the-art in biomedical data monitoring is limited in its modularity and relies on centralized computing models.