Impact of Radar, Voice-Assistants, and Robotics on the State of Elderly Care

Date: February 6, 2020

Author: Ipshita Biswas

Fall detection using Radar - PathPartner

Identified Issue – The growth prospects of the aging population worldwide.

The number of people aged 60 and above is expected to rise from 1 billion in 2015 to 2.1 billion in 2050, which is ultimately projected to reach 3.1 billion in 2100 (assuming nearly three times the number in 2017). The projections from the US Census Bureau have also suggested that by 2035, the number of individuals above 65 will be higher than the number of individuals under the age of 18.

With most seniors preferring to lead an independent life, giving their children the freedom to pursue their careers, it has become rather imperative to give way to innovations in the assisted living industry. In America alone, there’s a growing trend of individuals wishing to age in the comfort of their own homes rather than in a senior living facility. In order to prevent any major issues in the future, countries must prepare their healthcare monitoring and social protection for an aging population.

This article discusses some of the IoT-based solutions which have the potential to give elderly care a boost.

RADAR-based fall detection system

Fall detection using Radar - PathPartner

Falls have been identified as one of the leading causes of injury and death among older people as per data from Centres for Disease Control and Prevention. It further quotes the fact that more than 1/4 of older individuals fall each year and even fewer (half) of them tell their doctors. A portion of these falls result in serious injuries like broken bones or head injury. Falling, usually sideways, is the cause behind 95% of hip fractures. Needless to say, falls have stood out to be the most common cause of traumatic brain injury.

According to MarketsAndMarkets, “the overall fall detection system market is expected to be worth USD 497.3 million by 2022, growing at a CAGR of 5.58% between 2017 and 2022.”

There are a number of wearable devices designed conveniently to address the needs of either detecting falls or sending alerts. Some wearables offer automatic fall detection, while others require the individuals to press a push-button when falling. Alongside the prime functionality, some of the wearables offer a vital signs recognition ability and GPS tracking. Despite seeming like a convenient option, wearables haven’t been very successful so far in terms of being useful for the cause. As per a 2010 study published in the Journal of Gerontology and Geriatrics, out of all the people who purchase an emergency pendant, only about 14 percent wear it. The aversion of people having to constantly wear something around their wrist or neck hasn’t allowed the fall detection devices to meet their expectations. Other than this, wearables face other drawbacks of being battery operated and, of course, the associated social stigma. In short, the ‘passive, non-intrusive’ way of detecting a fall isn’t met here. According to a study conducted by NCBI, the chance of false alerts was higher in the case of wearables.

Deployment of camera-based sensors inside the house would solve the issue of having to remain in contact with a wearable and the chances of false alarms would also be averted as the visuals would be there. But camera-based sensors possess another challenge. Who would want to be under the camera 24/7? Nor would you like to see any of your family members deprived of this essential privacy. That’s where the use of accurate smart sensors come into play.

Here comes the role of Radar…

Radar (Radio Detection and Ranging) works on the principle of a source emitting radio waves (which travels at the speed of light), getting reflected off the surface of the object that falls on the path of the radio waves transmission, being received and processed by a receiver system.

PathPartner offers complete pipeline of radar algorithms as an SDK. The algorithms are suitable for various radar applications encompassing short range, medium range and long-range Scenarios. Our SDK package is readily available on leading radar sensors. However, it can be easily ported on any custom board.

Radar systems are non-intrusive technologies which can be conveniently placed anywhere from ceiling fans to doors/windows. Alongside detecting falls, PathPartner’s Radar SDK can be extended for a number of applications like Vitals Sensing, Breathing & Heart-Rate Monitoring, Medical Diagnosis.

Voice-assistants to make work easier

Voice-assistants are all set to play a major role in helping senior citizens lead independent lives. Besides sparing them the need to get up for trivial tasks like turning on the lights, AC, etc., the voice-assistants can be a further aid to their home security system. With Google, Amazon and Apple opening the doors to integrations with various types of devices, overall, lives have become easier. Voice-assistants have further diminished the dependency on domestic help.

Watch the demo our Alexa based device control

From setting up reminders for taking pills on time to communicating with your other home devices, voice-assistants can do them all. Apple HomeKit integration with home appliances and accessories has enabled the use of Siri to control them. Devices integrating with Alexa, Siri, and Cortana are on the rise and, very soon, with the right input from Machine Learning, their usability will increase manifold.

An insight into how IoT + Machine Learning is the gateway to a better world.

Elderly Care Robots

Robotics for elderly care - PathPartner

Sure, your Alexa can do a lot of tasks for you, but who will fetch you the pills if they aren’t kept nearby? How will you access your phone to get into a video call? That’s where the elderly care robots come into the picture.

The idea of robots taking care of the senior population has been there for years. But the growing gap between the number of available caregivers and the aging population has made the idea more relevant now. The issue of caregiver shortage has already started to bother Japan, where it’s predicted to have an estimated shortage of 1 million caregivers by 2025. The concern with elderly care further extends to its ever-increasing cost.

A national snapshot shows that the annual median cost of a private room in a nursing home is $92.378, which reflects a 1.24% increase from 2015.

The growing cost of elderly healthcare facilities combined with the shortage of the caregivers has been one of the prime forces behind the search for an efficient way to take care of the senior citizens.

The robots meant for elderly care would be equipped with powerful sensory and perception abilities combined with easy navigation and external integrations.

Japan is one of the first countries to invest into humanoid robotic solutions specifically for elderly care, a project well subsidized by the Japanese government. Similarly, in U.S. too government agencies are getting involved in incentivizing such efforts. Alongside the National Science Foundation investing in service robots, the National Institute of Health too is funding the robotics projects which focus on improvement of health and quality of life of the elderly.

The elderly care robots have a long way to go. Further, some parallel developments like the incorporation of machine learning would make them smarter and take autonomous decisions, addition of telepresence technology can enable social interaction between older people and their social groups, letting people to remain in touch from afar, using facial recognition technology to get an idea of someone’s mood or feelings which might leading to a pre-diagnosis tool at home.

Conclusion

It’s already hard to live away from parents, more so when they are aging and you are unable to be directly present around them. But, all thanks to the fast-evolving technological advances, surviving old age is no longer what it used to be.

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