Creating information automatically without burdening patients
EmPowerYu is a proprietary software platform that integrates Internet of Things (IoT) hardware from multiple manufacturers and creates a holistic and quantified view of daily life in the home. We use behavioral state modeling and an inference engine to understand the personal patterns of daily life for people who are not successfully monitored by other technologies. Our strategic sensor placement enables us to work in any floorplan, from studio apartments to multistory homes. Our automated data collection means we get 100% participation rates from people who are noncompliant with other technologies, whatever the reason.
Decide what data are needed
Find the best sensor to get those data in the real world
Personalize our Smart Home core sensor set as needed
Provide information to professional and family caregivers through a graphic user interface and numeric table of home metrics
Designing the Smart Home to support healthcare
Home security and home automation sensors automatically collect event data as patients go about their normal daily routines - like the use of the coffee pot, or timing and amount of activity in specific rooms like the bedroom or kitchen. EmPowerYu's algorithms use the sparse event data to detect essential patterns of daily life. We quantify the duration, timing, and distribution of events around eating, sleeping, activity, and use of devices, including medical devices and entertainment devices like a TV. Number-based descriptions allow us to run analytics on these daily events.
A family member knows that "when Grandpa misses his 9 am cup of coffee, there is a problem". So do we. We also know how much activity is normal for Grandma - we are like a FitBit for the home that can report whether she is active throughout the day, or is suddenly sitting all afternoon. We can see when Grandma's kitchen score shows that she is eating fewer and simpler meals.
How lifestyle context improves medical care
Medical device readings are a snapshot in physiological time. Clinicians have learned a lot about how readings change under different environmental conditions, and care decisions would greatly benefit from knowing the lifestyle context of home medical device readings. For example:
Blood pressure readings are affected by activity level before the measurement, so people are asked to sit quietly for 5-10 minutes before taking a baseline reading.
Blood glucose readings are directly related to the food eaten, activity level, and time since the last meal.
False alarms related to weight gain or loss are common because of differences in day-to-day weight changes related to clothing, meals, and toileting.
EmPowerYu shows the context of medical device readings on our visual dashboard, and we are currently constructing algorithms to normalize home medical device readings with lifestyle context. For example, we could reduce false alarms related to weight change by reporting the measured weight scale reading with a predictive reading that takes into account recency of a meal, toileting, and dressing. Or we could calculate the amount of activity in the 15 minutes prior to a blood pressure reading and report them together. Over time, characterizing the relationships between home medical device readings and life events would create a rich dataset to reduce misleading readings, to better understand what constitutes a 'normal' reading, and the effect of environmental conditions on those readings.
EmPowerYu system of proprietary software and open-platform IoT hardware
Flexibility and adaptability of an open platform
Technology changes very quickly, and EmPowerYu is ready to adapt. We choose the best available sensors to get the needed data, whereas competitors try to find applications for their own hardware. EmPowerYu's ecosystem is flexible and future-ready; it can incorporate new devices or new generations of devices as they become available. This design gives users and care providers the freedom to change or expand the hardware, while maintaining the power of a continuous data set.
Fall and stroke detection
EmPowerYu tracks inactivity and lack of expected activity, and can alert caregivers that a disabling problem may have occurred, such as a fall, a stroke, or an inability to get out of bed. Because EmPowerYu does not use cameras or other devices that watch a person constantly, it is not an emergency response system. For people who are willing and able to use it, a Personal Emergency Response system may provide additional reassurance.