Accession Number : ADA612520


Title :   Wearable Wireless Sensor for Multi-Scale Physiological Monitoring


Descriptive Note : Annual rept. 25 Sep 2013-24 Sep 2014


Corporate Author : WORCESTER POLYTECHNIC INST MA


Personal Author(s) : Chon, Ki H ; Mendelson, Yitzhak


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a612520.pdf


Report Date : Oct 2014


Pagination or Media Count : 82


Abstract : One of the aims of Year 2 of the project was to complete development of a prototype multi-channel pulse oximeter that can be used to collect physiological data from multiple body locations to combat motion artifact contamination. Specifically, the aim was to investigate if a motion artifact-free signal can be obtained in at least one of the multi-channels at any given time. Towards this aim, we have developed a prototype 6-photodetector reflectance-based pulse oximeter and results to date show that good signals can be obtained in one of the multi-channels at any given time. These devices are currently in use for field testing in our labs and at UMASS. Moreover, it was found that both forehead- and ear-located pulse oximeters provide better signal quality than a finger pulse oximeter. The second major aim of the project was to develop a motion and noise detection algorithm and a separate algorithm for the reconstruction of the motion and noise contaminated portion of the data. For detection of motion and noise artifacts, we have successfully developed an accurate and real-time realizable algorithm. For all new data including that from UMASS, our new MNA algorithms consistently provide better accuracy than our previously-published algorithm. A manuscript describing this new algorithm has been submitted for publication. In the past year, we have published 4 journal articles and 2 journal articles have been submitted based on algorithm development. Moreover, we have filed 2 new patent disclosures on our algorithms. Finally, we have recruited 105 patients to date at UMASS. These data will be used in the year 3 to investigate the robustness of our motion and noise artifact algorithms. Both the sensor and algorithms will be thoroughly tested and further refined, if needed, using the UMASS data collected in Year 3 of the project.


Descriptors :   *ALGORITHMS , *MONITORING , *PHOTODETECTORS , *VITAL SIGNS , HEMORRHAGE , MOTION DETECTORS , NOISE , PHOTODETECTION , PROTOTYPES , REMOTE DETECTORS , TIME , WIRELESS COMMUNICATIONS


Subject Categories : Anatomy and Physiology
      Medicine and Medical Research
      Numerical Mathematics
      Optical Detection and Detectors


Distribution Statement : APPROVED FOR PUBLIC RELEASE