Home monitoring using wearable radio frequency transmitters

被引:14
作者
Almudevar, Anthony [1 ]
Leibovici, Adrian [2 ]
Tentler, Aleksey [3 ]
机构
[1] Univ Rochester, Med Ctr, Dept Biostat & Computat Biol, Rochester, NY 14642 USA
[2] Univ Rochester, Med Ctr, Dept Psychiat, Rochester, NY 14642 USA
[3] Univ Rochester, Med Ctr, Ctr Future Hlth, Rochester, NY 14642 USA
关键词
motion tracking; wireless network; home monitoring; Gaussian mixture models;
D O I
10.1016/j.artmed.2007.11.002
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Background: Location tracking of a wearable radio frequency (RF) transmitter in a wireless network is a potentially useful tool for the home monitoring of patients in clinical applications. However, the problem of converting RF signals into accurate estimates of transmitter location remains a significant challenge. Objectives: We wish to demonstrate that tong-term home monitoring using RF transmitters is feasible. Additionally, we conjecture that human motion within familiar environments is confined to relatively small regions of high occupancy. Hence, human motion can be modelled as movement along a network of such high occupancy regions. Methods and materials: Our methodology uses a signal processing technique developed by one of the authors (Almudevar). The technique converts longitudinal RF data into an estimated trajectory which does not depend on explicit location estimates. This approach eliminates the need for a location-signal calibration procedure. Given a long-term trajectory, Gaussian mixture models are used to identify high occupancy regions. The methodology was evaluated using data collected under a study funded by an Everyday Technologies for Alzheimer Care (ETAC) research grant from the Alzheimer's Association. A home monitoring system provided by Home Free Systems was used. Results: The proposed methodology was able to reliably reconstruct trajectories using study data. Regions of high occupancy were identified, and the observed transitions between these regions were found to be spatially and serially coherent. In addition, the trajectory was compared to output from a parallel home sensor network, and a high degree a conformity was evident. Conclusion: Long-term home monitoring of human motion is feasible using readily available and easily installable technology. Furthermore, by using suitable signal processing algorithms, the often difficult location-signal calibration process can be bypassed. (C) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码:109 / 120
页数:12
相关论文
共 23 条
[1]   A mixture model approach for the analysis of microarray gene expression data [J].
Allison, DB ;
Gadbury, GL ;
Heo, MS ;
Fernández, JR ;
Lee, CK ;
Prolla, TA ;
Weindruch, R .
COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2002, 39 (01) :1-20
[2]  
ALMUDEVAR A, IN PRESS IEEE T SIG
[3]   Malguki:: an RSSI based ad hoc location algorithm [J].
Arias, J ;
Zuloaga, A ;
Lázaro, J ;
Andreu, J ;
Astarloa, A .
MICROPROCESSORS AND MICROSYSTEMS, 2004, 28 (08) :403-409
[4]  
Bahl P., 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064), P775, DOI 10.1109/INFCOM.2000.832252
[5]   Health-status monitoring through analysis of behavioral patterns [J].
Barger, TS ;
Brown, DE ;
Alwan, M .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, 2005, 35 (01) :22-27
[6]   MAXIMUM LIKELIHOOD FROM INCOMPLETE DATA VIA EM ALGORITHM [J].
DEMPSTER, AP ;
LAIRD, NM ;
RUBIN, DB .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-METHODOLOGICAL, 1977, 39 (01) :1-38
[7]   Positioning and navigation with applications to communications [J].
Dogandzic, A ;
Riba, J ;
Seco, G ;
Swindlehurst, AL .
IEEE SIGNAL PROCESSING MAGAZINE, 2005, 22 (04) :10-11
[8]   Unsupervised learning of finite mixture models [J].
Figueiredo, MAT ;
Jain, AK .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2002, 24 (03) :381-396
[9]   Localization via ultra-wideband radios [J].
Gezici, S ;
Tian, Z ;
Giannakis, GB ;
Kobayashi, H ;
Molisch, AF ;
Poor, HV ;
Sahinoglu, Z .
IEEE SIGNAL PROCESSING MAGAZINE, 2005, 22 (04) :70-84
[10]   Mobile positioning using wireless networks [J].
Gustafsson, F ;
Gunnarsson, F .
IEEE SIGNAL PROCESSING MAGAZINE, 2005, 22 (04) :41-53