Technology & Aging

An Interdisciplinary Approach to Promote Older Adult Health Over twenty years ago, the University of Missouri formed a broad interdisciplinary team to revolutionize older adult care. Over the years, this team consisted of engineering, nursing, and social work researchers,...

Early detection of health changes among older adults is the key to maintaining health, independence, and function. Non-wearable sensors such as depth cameras, motion sensors (passive infrared, PIR) and bed sensors (based on ballistocardiography) are able to detect changes...

Objectives: Measure the clinical effectiveness and cost-effectiveness of using sensor data from an environmentally embedded sensor system for early illness recognition. This sensor system has demonstrated in pilot studies to detect changes in function and in chronic diseases or...

A set of metrics and a methodology were developed to characterize a subject’s ability to ambulate. These metrics use the movement of the subject’s centroid as detected by an inexpensive depth camera system. The centroid is chosen as it...

In this paper, we propose a Pulse-Doppler radar system for in-home gait assessment of older adults. A methodology has been developed to extract gait parameters including walking speed and step time using Doppler radar. The gait parameters have been...

When planning the Aging in Place Initiative at TigerPlace, it was envisioned that advances in technology research had the potential to enable early intervention in health changes that could assist in proactive management of health for older adults and...

Gait parameters variability and falls are problems for persons with MS and have not been adequately captured in the home. Our goal was to explore the feasibility and acceptability of monitoring of gait and falls in the homes of...

Gait impairment represents one of the most common and disabling symptoms of multiple sclerosis (MS). To identify which temporal or spatial parameters of gait could be used as outcome measures in interventional studies of individuals with MS with different...

Introduction With the increase in the population of older adults around the world, a significant amount of work has been done on in-home sensor technology to aid the elderly age independently. However, due to the large amounts of data...

This study explored using Big Data, totaling 66 terabytes over 10 years, captured from sensor systems installed in independent living apartments to predict falls from pre-fall changes in residents’ Kinect-recorded gait parameters. Over a period of 3 to 48...