Specific Aims. Development and Acceptability of an Ambient In-Home Activity Assessment Tool for Stroke Stroke is the leading cause of serious, long-term disability in the United States . Every year, approximately 800,000 people experience a new or recurrent stroke . Due to advances in acute neurological care, nearly 85% survive and many live with the […]
Sensing technologies hold enormous potential for early detection of health changes that can dramatically affect the aging experience. Embedded health assessment can enable functional independence, improve self-management of chronic or acute conditions, and thus, improve quality of life
Sensing technologies hold enormous potential for detecting and tracking health changes that can dramatically affect the aging experience. Embedded health assessment can improve management of chronic or acute conditions, and thus, improve quality of life. Problems in chronic disease management are often the cause of losing independence for aging Americans.
Extracting information from the sensors installed in the homes of elderly pose a unique set of challenges. Add to it the short amount of time the clinicians and nurses have to analyze this data, and the problem becomes more complicated. The ongoing work in this project focuses on development of algorithms to glean information from in-home sensor data and then presenting it in the form of textual summaries using Natural Language Generation techniques.
We are developing an application to automate data collection for the physical function assessments that are normally measured manually by physical therapists or nurses. The assessment tool will be used every 6 months to assess older adults’ functional movement and range of motion as part of the Health Kiosk project.
We have tested our monitoring and health alert system in TigerPlace, an aging in place facility near the University of Missouri campus in Columbia, MO and, more recently, in assisted living in Cedar Falls, IA. The proposed project will build on this work with an innovative, interactive healthcare service. The monitoring system with health alerts will be introduced into independent housing in Kansas City. A new interactive exercise coaching interface will connect a remote physical therapist to senior clients in the home. GENI-enabled networking will be incorporated to support interactive monitoring and coaching that operates in real-time.
This project is a collaboration between three different disciplines: Music, Engineering and Health Science. The long-term goal is to develop strategies for injury-prevention in undergraduate piano students. Common causes of injury among young pianists are: skeletal misalignment, excessive muscular tension and repetitive stress injury.
In this randomized controlled study, we are investigating and refining health alerts produced by environmentally-embedded in-home sensor networks designed to detect early signs of health change and functional decline in older adults, the keys to successful intervention.
The general objective is to develop and test a prototype ACL Gold computer software utilizing the Microsoft Kinect motion sensor that includes a screening tool and intervention to help prevent ACL tears in female youth athletes. The program measures the knee abduction angle during specific jumping and cutting tasks.
In this project, we test the concept in senior housing in Cedar Falls, Iowa, using in-home sensors and remote video conferencing for the nurse care coordination. Fiber networking in Columbia and Cedar Falls will provide the bandwidth and latency essential for this approach. Previous system development is utilized and a new hydraulic bed sensor has been integrated. The sensor configuration also includes the team’s previous work with the Kinect depth images for extracting gait parameters of residents in the home.
The main goal of this work was to develop algorithms for early illness recognition in elderly. Early illness recognition (EIR) is important, as research has shown that results in better medical outcomes and a reduction in health care cost. We developed methodologies (see Figure 1) that link sensor data to the medical (nursing) records for monitoring the residents of TigerPlace, an aging in place community from Columbia, Missouri.
Human subject experiments will be conducted with college students and elderly participants to explore spatial descriptions in a fetch task; results will drive the development of robot algorithms, which will be evaluated using a similar set of assessment experiments in virtual and physical environments.
Building on our current work, we propose to validate and deploy an innovative technological approach that automatically detects when falls have occurred or when the risk of falls is increasing. Subjects will not have to press buttons, pull cords or wear any devices. This new “passive” approach using sensors in the home could revolutionize detecting and preventing falls as well as measuring fall risk.
We leverage ongoing research at a unique local eldercare facility (TigerPlace) to study active sensing and fusion using vision and acoustic sensors for the continuous assessment of a resident’s risk of falling as well as the reliable detection of falls in the home environment. The project investigates the interplay between fall detection and fall risk assessment.
Researchers at the University of Missouri-Columbia and the University of Washington have established a multidisciplinary team comprised of researchers in computer science and engineering, nursing, and medical informatics dedicated to developing and evaluating technology to keep older adults functioning at higher levels and living independently. We have leveraged ongoing research at a unique local eldercare facility (TigerPlace) to study vision-based recognition methods for multi-person environments designed to capture continuous and automated assessments of older adults’ physical function.
We propose a carpet with pressure sensors distributed throughout the floor with an average of 10 sensors per square foot sheet; these will be incorporated onto flooring material such as carpeting, flexible tiles or linoleum. We will be able to “see” the person’s footsteps, assess their gait, and identify their location.
Our objective is to explore new information technologies to assist the independent living of elderly people and enhance their quality of life at home, while utilizing the time and attention of caregivers and eldercare specialists in the highest efficiency.
The overall objective of our RAND/Harford Interdisciplinary Geriatric Health Care Research Center is to promote interdisciplinary research with a special focus on development of innovative clinical and health services interventions for older adults. We will impart to junior faculty and graduate students the needed attitudes, knowledge, and skills for conducting relevant interdisciplinary research related.
The dream of older Americans is to remain as active and independent as possible for as long as possible. They want to age in place, not in institutions like nursing homes. Recently, enabling technology in the form of low cost sensors, computers, and communications systems has become available, which with supportive health care services makes the dream of aging in place a reality.
Americans are living longer and more fulfilled lives, and they desire to live as independently as possible. But independent lifestyles come with risks. To address these issues, researchers are developing “smart home” technologies to help older adults remain independent at home while controlling costs. Smart homes enhance residents’ safety and monitor health conditions using sensors and other devices. Such technology can help keep older adults independent while controlling costs.