Remote Health Monitoring for Older Adults and Those with Heart Failure: Adherence and System Usability.

BACKGROUND: Remote health monitoring technology has been suggested as part of an early intervention and prevention care model. Older adults with a chronic health condition have been shown to benefit from remote monitoring but often have challenges with complex technology. The current study reports on the usability of and adherence with an integrated, real-time monitoring system over an extended period of time by older adults with and without a chronic health condition. MATERIALS AND METHODS: Older adults 55 years of age and over with and without heart failure participated in a study in which a telehealth system was used for 6 months each. The system consisted of a wireless wristwatch-based monitoring device that continuously collected temperature and motion data. Other health information was collected daily using a weight scale, blood pressure cuff, and tablet that participants used for health surveys. Data were automatically analyzed and summarized by the system and presented to study nurses. RESULTS: Forty-one older adults participated. Seventy-one percent of surveys, 75% of blood pressure readings, and 81% of daily weight measurements were taken. Participants wore the watch monitor 77% of the overall 24/7 time requested. The weight scale had the highest usability rating in both groups. The groups did not otherwise differ on device usage. CONCLUSIONS: The findings indicate that a health monitoring system designed for older adults can and will be used for an extended period of time and may help older adults with chronic conditions reside longer in their own homes in partnership with the healthcare system.

Metrics for assessing the reliability of a telemedicine remote monitoring system.

OBJECTIVE: The goal of this study was to assess using new metrics the reliability of a real-time health monitoring system in homes of older adults. MATERIALS AND METHODS: The "MobileCare Monitor" system was installed into the homes of nine older adults >75 years of age for a 2-week period. The system consisted of a wireless wristwatch-based monitoring system containing sensors for location, temperature, and impacts and a "panic" button that was connected through a mesh network to third-party wireless devices (blood pressure cuff, pulse oximeter, weight scale, and a survey-administering device). To assess system reliability, daily phone calls instructed participants to conduct system tests and reminded them to fill out surveys and daily diaries. Phone reports and participant diary entries were checked against data received at a secure server. RESULTS: Reliability metrics assessed overall system reliability, data concurrence, study effectiveness, and system usability. Except for the pulse oximeter, system reliability metrics varied between 73% and 92%. Data concurrence for proximal and distal readings exceeded 88%. System usability following the pulse oximeter firmware update varied between 82% and 97%. An estimate of watch-wearing adherence within the home was quite high, about 80%, although given the inability to assess watch-wearing when a participant left the house, adherence likely exceeded the 10 h/day requested time. In total, 3,436 of 3,906 potential measurements were obtained, indicating a study effectiveness of 88%. CONCLUSIONS: The system was quite effective in providing accurate remote health data. The different system reliability measures identify important error sources in remote monitoring systems.

Usability Enhancements to a Prototype Clinical Decision Support System for Combat Medics.

INTRODUCTION: A Clinical Decision Support System that provides just-in-time medical guidance at the point of injury is being developed. To develop a user interface, a user-centered design approach was taken. MATERIALS AND METHODS: To evaluate the system, personas of the users were created, a comparative analysis of the system against the Tactical Combat Casualty Care Card and Battlefield Assisted Trauma Distributed Observation Kit was completed, and user testing was performed. RESULTS: Many design recommendations were gathered from the user-centered design approach including replacing buttons with a homunculus, replacing prompts with a tree and node system, and allowing more user freedom in working with the system. CONCLUSIONS: Through multiple different evaluations, design recommendations for a clinical decision support system were implemented in an iterative process. More iterations and more formalized user testing are planned to maximize the usability of the system.

Differentiating Walking from other Activities of Daily Living in Older Adults Using Wrist-based Accelerometers.

There is a significant body of literature demonstrating that accelerometers placed at various locations on the body can provide the data necessary to recognize walking. Most of the literature, however, either does not consider accelerometers placed at the wrist, or suggests that the wrist is not the ideal location. The wrist, however, is probably the most socially-acceptable location for a monitoring device. This study evaluates the possibility of using wrist accelerometers to recognize walking in the elderly during everyday life to evaluate the amount of time spent walking and, moreover, potentially recognize changes in stability that might lead to falls. Thirty elderly individuals aged 65 years and older were asked to wear a wrist accelerometer for four hours each while simultaneously being video recorded as they went about their normal daily activities. Accelerometer data were then analyzed using both frequency- and time-domain analyses. Particular attention was given to methods capable of being calculated on the wrist device so that future work will not require streaming large amounts of data from the device to the central server. Frequency based analysis to characterize walking in the test set yielded results of 98% area under the receiver operating characteristic curve (AUC). Using a time-series algorithm limited to features calculable on the wrist device, moreover, achieved an AUC of 90%. A small, socially-acceptable, wrist-based device, therefore, can successfully be used to differentiate walking from other activities of daily living in older adults. These findings may enable improved gait monitoring and efforts in falls prevention.