Wearable Flags Health Changes in Seniors Via Biosensors and Predictive Analytics

Wearable Flags Health Changes in Seniors Via Biosensors and Predictive Analytics

If you've got a parent, grandparent, or other older loved ones in your life who aren't living with you, it might be challenging to feel assured that they're doing well. Changes in diet and other behaviors that could indicate a health concern might be too subtle to notice during a periodic visit. And with the COVID-19 pandemic continuing to disrupt family visits—or even making them impossible in some cases—it has become that much harder to assess the well-being of seniors.

CarePredict has a solution: a digital health platform that utilizes its Tempo wearable, which monitors pulse oximetry and heart rate, along with precise location sensors to track the behavior, patterns, and deviations of each user. Headquartered near Fort Lauderdale, Florida, CarePredict was founded in 2013 by Satish Movva, the company's CEO. He was inspired to create the monitoring system after he began noticing new health-related concerns in his elderly parents during weekly visits.

Now that multigenerational households are less common, Movva noted, "We've become that continuous observation platform for elders aging away from their family."

The CarePredict system is being used in senior living facilities and private homes. It utilizes biosensors, deep learning algorithms, and predictive analytics to provide actionable insights to caregivers. The system can help predict conditions like urinary tract infections, depression, or fall risks, and trigger early interventions.

The CarePredict digital health platform featuring the Tempo wearable uses biosensors, artificial intelligence, and predictive analytics to derive actionable insights to enhance care and quality of life for seniors.

What differentiates the CarePredict system from older technologies like motion sensors is that these legacy solutions aren't able to provide detailed insights other than, say, motion tracking. By contrast, the CarePredict platform tracks where the wearer is, whether that's a bedroom, the kitchen, or a bathroom. It has the intelligence to, over time, learn the daily tempo of each user, detecting and reporting behavioral shifts to trigger early intervention. Worn on the dominant arm, the Tempo wearable uses gesture recognition to identify various activities, such as when the wearer is lifting a fork to their mouth. Through the push of a button on the device, wearers can contact a caregiver or, with the home version, speak to a family member. An associated app provides families "a detailed understanding of how their loved one is doing day to day. Did they skip a meal or two today? Are they being less active than they used to be?" explained Movva.

To create the CarePredict platform, the company needed accurate biosensors and fuel gauges, power-efficient switching regulators, and high-performing audio amplifiers. The Tempo wearable is compact and battery powered, so the components also needed to support its small footprint and expected long runtime. During its IC evaluation process, CarePredict began working with Maxim Ventures, which invests in healthcare and life sciences startups. Through this collaboration, the team found the support as well as Maxim ICs with which to build their platform:

  • MAXM86146 optical sensor module with integrated algorithms
  • MAX20343 ultra-low quiescent current, low-noise 3.5W buck-boost regulator for wearables and IoT designs
  • MAX14689 ultra-small, Beyond-the-RailsTm DPDT analog switch
  • MAX98357 digital pulse-code modulation input Class D amplifier, which provides Class AB audio performance with Class D efficiency
  • MAX16125 dual pushbutton controllers
  • MAX17055 7µA, 1-cell fuel gauge with ModelGaugeTm m5 EZ algorithm on the Tempo's battery pack
  • MAX17201 stand-alone ModelGauge m5 fuel gauge with SHA-256 authentication on the system's room beacon

"All of our devices use Maxim fuel gauges because they're the most accurate," said Movva."There are lots of heart-rate sensors out there, but their quality in terms of accuracy isn't there. Maxim showed us what is possible, and really pulled out all the stops. The parts are really fantastic, are quick and easy to design with, and have low power consumption, high accuracy, and form factors that are perfect for our kind of wearable."

A sensor module such as the one inside the Tempo wearable typically requires at least a year to incorporate into a design. Movva noted that CarePredict's sensor module was completed in just six weeks, which gave the company additional time to refine their solution.

In response to the COVID-19 pandemic, CarePredict has created a contact-tracing capability using its location-tracking technology. Designed for care facilities, the CarePredict PinPoint system identifies within seconds all of the individuals and places that an infected person has come into contact with. The company also plans to explore respiration rate monitoring, a capability that could further help in the care of COVID-19 patients and well as those with other respiratory illnesses.

"We're helping seniors live longer, safer, healthier lives, and giving families peace of mind," said Movva.

This blog post was adapted from the CarePredict customer testimonial.