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An algorithm has been developed to automatically construct individual models of normal activity within a home using motion sensor data. Alerts can be generated when a period of inactivity exceeds a normal length for a particular residence. Alerting frequency has been optimized on a total of 650 days of real data from four homes of seniors who live(More)
Falling is a common health problem for elderly. It is reported that more than one third of adults 65 and older fall each year in the United States. To address the problem, we are currently developing a Doppler radar-based fall detection system. Doppler radar sensors provide an inexpensive way to recognize human activity. In this paper, we employed(More)
Falls are a major cause of injury in the elderly with almost 1/3<sup>rd</sup> of people aged 65 and more falling each year [1]. This work aims to use gait measurements from everyday living environments to estimate risk of falling and enable improved interventions. For this purpose, we consider the use of low-cost pulse-Doppler range control radar. These(More)
Seniors want to live more independent lifestyles. This comes with some risks including dwindling health and major injuries due to falling. A factor that has been studied and seen to have a correlation to fall risk is change in gait speed. Our goal is to create a passive system that monitors the gait of elderly so that assessments can be given by caregivers(More)
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 validated with a Vicon motion capture system in the lab with 13 participants and 158 test runs. The study(More)
Falls are a significant cause of injury and accidental death among persons over the age of 65. Gait velocity is one of the parameters which have been correlated to the risk of falling. We aim to build a system which monitors gait in seniors and reports any changes to caregivers, who can then perform a clinical assessment and perform corrective and(More)
Two sensing options are examined for their potential to improve the sensitivity of a system that detects periods of inactivity in the homes of elderly persons. A previous prototype used passive infrared motion sensors and door sensors combined with a learning algorithm to detect periods of unusual inactivity such as late wake-ups or the aftermath of a fall.(More)
With the advent of Big Data technologies, organizations can efficiently store and analyze more data than ever before. However, extracting maximal value from this data can be challenging for many reasons. For example, datasets are often not stored using human-understandable terms, making it difficult for a large set of users to benefit from them. Further,(More)