Robert Hammond

University of Michigan, Ann Arbor, Michigan, United States

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Publications (3)1.6 Total impact

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    ABSTRACT: The current state of the art approach to preventing falls of hospitalized elderly adults with dementia is to use a video surveillance setup in each of the hospital rooms and have hospital personnel continuously monitor the video feeds. In this research, we are developing a motion monitoring system to reduce the number of accidental falls among patients at acute risk, while preserving their privacy. The prototypical system includes five accelerometer-based wireless sensors that are placed on the wrists, ankles, and chest of a patient. The system senses the movements and postures of the patient and transmits the information wirelessly to a remote base station. The received motion information is processed in real-time and used to animate a 3D avatar that figuratively represents the movements of the patient. The 3D avatar is intended to give care staff early warning of patient wakefulness, agitation, and of patients attempt to arise from the bed without assistance, while preserving the privacy of the patients. This research also aims to develop predicative algorithms to detect fall-antecedent activity and provide an early warning to care personnel. The base station keeps the captured video and the received motion information synchronized in time and stores them together into a database. The stored video and motion information can be played back in time to plot the motion information as real-time signals on a screen that is synchronized with the captured video of the patient. This paper provides background, motivation, and current state of the art approaches to reducing falls in hospitals. Our prototypical system has undergone preliminary testing successfully on several elderly patients at William Beaumont Hospital at Royal Oak, MI, USA.
    01/2012;
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    ABSTRACT: The purpose of this pilot study was to test the feasibility of a wireless 5-sensor, motion detection system (5S-MDS) with hospitalized older adults. Interventions to prevent hospital-based falls in older adults are important to reduce morbidity, mortality, and health care costs. Wearable motion sensors, which track and wirelessly transmit body movements, may identify human movement patterns that immediately precede falls, thus allowing early prevention. Descriptive feasibility study in which 5 hospitalized older adults were recruited to wear the 5S-MDS for 4 hours. Measurement included assessment of participant acceptance, skin integrity, and sensor accuracy. All 5 participants (mean age, 90.2 years) agreed that sensors were acceptable and skin integrity was maintained. The sensor data accurately reflected the patient movements. The 5S-MDS was feasible for 4 hours' use with hospitalized older adults. It has potential as an early warning system for falls.
    Geriatric nursing (New York, N.Y.) 12/2011; 33(3):177-83. · 0.79 Impact Factor
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    ABSTRACT: Interventions to prevent hospital-based falls in older adults are critically important to reduce morbidity, mortality, and health care costs. The purpose of this pilot study was to test the accuracy and acceptability of a wireless five-sensor motion detection system (5S-MDS) for detecting falls. Wearable motion sensors, which measure and integrate movement in space, may identify human movement patterns that immediately precede falls, thus allowing prevention. However, sensors must be accurate, and older adults must find wearable sensors acceptable. This descriptive feasibility study recruited 5 healthy older adults (mean age = 69.6) who wore the 5S-MDS while performing 35 movement scenarios. All participants agreed the sensors were acceptable, and skin integrity was maintained for all. The 5S-MDS accurately reflected the patients' movements and was found acceptable to the older adults; thus, the 5S-MDS has potential as an early warning system for falls.
    Journal of Gerontological Nursing 12/2011; 38(1):13-6. · 0.81 Impact Factor