Sleeping posture reveals important information for eldercare and patient care, especially for bed ridden patients. Traditionally, some works address the problem from either pressure sensor or video image. This paper presents a multimodal approach to sleeping posture classification. Features from pressure sensor map and video image have been proposed in order to characterize the posture patterns. The spatiotemporal registration of the two modalities has been considered in the design, and the joint feature extraction and data fusion is presented. Using multi-class SVM, experiment results demonstrate that the multimodal approach achieves better performance than the approaches using single modal sensing.

Due to the physical and mental impairments, frail elderly have to stay in the bed most of their time. So, serious health issues and physical injuries can occur to them if dangerous events and situations around the bed are not known in advance. This paper proposes continuous patient monitoring with situation awareness using multimodality sensors to recognize such dangerous events in and around the bed. With multimodal sensing intelligence, various contexts and situations of those bedridden elderly can be determined. By incorporating personalization and medical domain knowledge into detected events and activities, dangerous events can be recognized immediately. Then, timely intervention can be provided to the elderly with potential fall risks. So our solution supports situation aware patient monitoring and provides desirable personalized care at the institutions enabling to prevent potential health and well-being problems in and around the bed.

article Free Access Share on PIPE: a VLSI decoupled architecture Authors: J. R. Goodman The University of Wisconsin-Madison, Computer Sciences Department, 1210 W. Dayton St., Madison, WI The University of Wisconsin-Madison, Computer Sciences Department, 1210 W. Dayton St., Madison, WIView Profile , Jian-tu Hsieh The University of Wisconsin-Madison, Computer Sciences Department, 1210 W. Dayton St., Madison, WI The University of Wisconsin-Madison, Computer Sciences Department, 1210 W. Dayton St., Madison, WIView Profile , Koujuch Liou The University of Wisconsin-Madison, Computer Sciences Department, 1210 W. Dayton St., Madison, WI The University of Wisconsin-Madison, Computer Sciences Department, 1210 W. Dayton St., Madison, WIView Profile , Andrew R. Pleszkun The University of Wisconsin-Madison, Computer Sciences Department, 1210 W. Dayton St., Madison, WI The University of Wisconsin-Madison, Computer Sciences Department, 1210 W. Dayton St., Madison, WIView Profile , P. B. Schechter The University of Wisconsin-Madison, Computer Sciences Department, 1210 W. Dayton St., Madison, WI The University of Wisconsin-Madison, Computer Sciences Department, 1210 W. Dayton St., Madison, WIView Profile , Honesty C. Young The University of Wisconsin-Madison, Computer Sciences Department, 1210 W. Dayton St., Madison, WI The University of Wisconsin-Madison, Computer Sciences Department, 1210 W. Dayton St., Madison, WIView Profile Authors Info & Claims ACM SIGARCH Computer Architecture NewsVolume 13Issue 3June 1985 pp 20–27https://doi.org/10.1145/327070.327117Published:01 June 1985Publication History 101citation592DownloadsMetricsTotal Citations101Total Downloads592Last 12 Months50Last 6 weeks13 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF