Artificial Intelligence: The future of elderly care?

Kelly Franklin’s father Donald, a devoted Air Force veteran, is 82 years old. One morning, kelly recalls, her father tried to make breakfast for himself, only to mess up the house. Seven open boxes of cereal lay on the living room floor, and milk was poured straight into them. Donald was later diagnosed with moderate to severe dementia.
Carrie, 40, is Donald’s only child and his primary carer. But Kelly now doesn’t have to worry about a repeat.
Kelly lives with her father in a townhouse in Inglewood, Los Angeles. In late 2019, Kelly installed motion sensors connected to an ARTIFICIAL intelligence system in her home. Sensors at the top of each door and in parts of the room monitor their movements, tracking their daily behavior patterns. If her father deviates from normal behavior, such as leaving the house and not coming home immediately, the sensor sends an alert to Kelly’s phone.
“If it had been like that morning, I would have been alerted as soon as he walked into the kitchen,” Kelly said. Because as far as Donald is concerned, “going into the kitchen” is unusual, especially early in the morning. Kelly says the ai system has taken the burden of caring for her father around the clock a little less and has helped her stay “sane.”
This is nursing care in the 2020s! In rich societies, where populations are ageing, many families still want older people to stay at home, but there is a shortage of carers. Driven by these three factors, the computer has gradually assumed the task of nursing for the aged. So-called “eldertech” companies have sprung up in the past few years, offering monitoring technology that focuses on older people with cognitive decline. Solutions from such companies have trickled down into home care, assisted care and specialized care facilities.
Majid Alwan, executive director of the Center for Eldercare Technology at the National Association for Eldercare, a group that represents nonprofit providers, concluded that technology could liberate human caregivers and make them more efficient.
| | to protect the safety of the elderly

In terms of keeping older people safe and giving carers a break, technology can help. Still, there are concerns about the potential harm. They raised questions about the accuracy, privacy and licensing agreements of the pension system, and raised questions about what kind of world we want for the elderly. Alyssa Grigorovich, a gerontologist at the Rehabilitation Institute of Toronto, part of the University of Toronto Health Network, has been studying the technology. “People may think that these plans are better than the old ones, and I think that’s an assumption,” grigorovich said.
Technology has been used for years to keep the elderly safe, from life warning pendants to “hidden cameras” installed in homes for fear of abuse by babysitters. But the application of ARTIFICIAL intelligence has never been done before. Cheap sensors are constantly collecting data that can be analysed to identify patterns of behaviour in everyday activities and determine whether certain behaviours are deviant.
Falls, wandering behaviour and changes in the frequency and duration of toilet visits can all signal health problems such as urinary tract infections or dehydration that need to be alerted to a carer. Some systems can monitor space using a variety of devices, such as motion sensors, cameras and even lidar, commonly used in self-driving cars. Some systems also monitor individuals through wearable devices.
CarePredict is a watch-like device that is worn on the user’s dominant arm. By studying gesture patterns and other data, the device can track specific activities that individuals are likely to engage in. Carers are alerted if repeated eating behaviour is not detected as expected. If the system recognizes that the user is in the bathroom and detects that the person is sitting, it can infer that the person is “using the bathroom,” according to the patent description.
The system Kelly uses is called People Power Family. The system has an add-on for nursing facilities that tracks and reports on a daily basis when someone falls asleep, whether they bathe, how many times they go to the bathroom, and so on. “You can rely on fewer caregivers to care for more clients,” says a promotional video for the system.
Trousdale is a paying senior living community in Silicon Valley, where studio apartments start at $7,000 a month. In the three-story care area for the mentally disabled, a large blue warning sign says “Fall prevention video surveillance activated.”
SafelyYou, a Startup based in the San Francisco Bay Area, has developed ai-based fall detection technology. In late 2019, the Community of Trousdale deployed the technology in 23 apartment suites in its care for the mentally disabled. Unobtrusive cameras, mounted high on the walls of each bedroom, constantly monitor the room.
As more data is available on falls, the system is being refined. If the system detects a fall, it alerts the staff. Surveillance video is saved if and only if a fall event triggers the system. Carers in the Community control room in Trousdale then review the video to determine whether the elderly person has hit his head and needs to go to hospital, and a dedicated staff member analyzes what changes the community needs to make to prevent the elderly person from falling again.
Is of great importance to improve | | potential problems

“There’s probably an 80 percent reduction in falls in our community,” said Sylvia Chu, executive director of the Community of Trousdale. The system caught every fall she knew of, but she added that it sometimes turned out elderly people were lying on their faces on purpose, possibly looking for something they had dropped. “I don’t want to call it a false warning, but it wasn’t a fall.” Chu said. However, she stressed that this was not a problem as elderly people would normally need help getting back up and staff were happy to help.
“We’re still at the surface of the problem,” said SafelyYou founder and CEO George Natcher, referring to the accuracy of the system. The company refers to “non-fall events” as “ground events.” Taking kneeling to pray as an example, Natcher points out that 40 percent of system-triggered events are actually “ground events.” While the company wants to reduce its error rate, Mr. Necher says it’s better to be safe than sorry.
Pension technology companies must also consider bias. The optimization of ai models relies on databases that monitor the behavior of past objects, which means that databases cannot capture everyone and every situation. Bisent Ordonez-Roman, a computer vision technology expert at the University of Virginia, says there is ample evidence that the same gender and racial discrimination that exists in other AI-based technologies may also exist in retirement services.

There is also cultural bias. CarePredict, which monitors eating behavior, recently entered the Japanese market, but the team didn’t adapt it for people who use chopsticks rather than forks. Satish Merwa, the company’s founder and CHIEF executive, says they have built this into their plans.
Clara Berridge of the University of Washington has been studying the impact of digital technologies used in elderly care. Encroachment on older people’s privacy is one of the most worrying risks, she says. She also worries that the use of digital technology will reduce human interaction and hands-on care, which is already happening in many fields, and that this could lead to older people becoming more isolated from society.
In 2014, Berridge interviewed 20 older adults without cognitive impairment who lived in the same freestanding apartment building. The building is aimed at low-income people and is equipped with QuietCare, an AI-based motion monitoring system. If something unexpected happens, such as a fall in the bathroom, a failure to get out of the bedroom, a decrease in total activity or a significant change in nighttime toilet habits, the monitoring system will tell the operator to call the elderly person and, if necessary, contact their family.

The preset daily behavior patterns in the system disrupt older people’s activities, forcing them to change their habits to avoid triggering unnecessary alarms that disturb their families.

Berridge, however, found “guilt” in the surveillance system. The preset daily behavior patterns in the system disrupt older people’s activities, forcing them to change their habits to avoid triggering unnecessary alarms that disturb their families. One elderly woman stopped sleeping in her recliner because she feared the system would warn her that she was not active enough. There are also old people who always rush to the bathroom, not wanting to get in trouble by staying too long.
Some asked for the sensors to be removed, but others were so lonely they played games with the system so they could chat with the operators.
QuietCare is being developed by PRA Health Sciences. A spokesman for the company said that Mr. Berridge looked at historical versions of the system in his paper, and that the latest version was only installed in assisted care facilities. If the user’s behavior pattern changes or deviates from the norm, the system will notify the staff of the assisted care facility rather than the user’s family.
Berridge’s interview revealed other concerns. There is evidence of good-faith coercion of older people by social workers and family members in order to get them to accept monitoring techniques. Such coercion, Berridge says, “can lead to conflict.” Another of her studies found that older adults and their adult children were much more enthusiastic about home monitoring systems.
Sometimes, though, older people’s opinions prevail. Cherry Labs, a start-up, turned its business around in part because it had trouble getting permission from older people. Cherry Home, the company’s Home monitoring system, has up to six recording AI cameras that can pick up worrying behaviour and raise an alarm, can identify people in the space other than the user using facial recognition technology, and can allow family members or carers to follow the elderly in real time. However, Max Goncharov, the company’s co-founder and CEO, says their business has been difficult to get off the ground, largely because adult children can’t convince their parents to accept the monitoring system. “The elderly are against the monitoring system.” “Said Goncharov. Now Cherry Labs is working on another app to bring the technology to industrial workshops that want to monitor employee safety.
Kelly says her home monitoring system is equipped with motion sensors rather than cameras, which she thinks is crucial. Kelly and Donald are both African-American, and she simply doesn’t believe her father can live comfortably under the surveillance of cameras. “My father was born in the South in 1940, and he saw the development and regression of race,” she said. He must be carrying some trauma. He was deeply suspicious of many aspects of our American culture.”
Kelly explained the monitoring system to Donald as best she could in simple language, without trying to embellish it. For the most part, he was happy to do anything he could to help Kelly. Kelly now pays $40 a month for her home monitoring system.
“I don’t want to be a burden.” Donald said. Still, he wants her to know that if they find the monitoring system too intrusive, he has a plan. Donald said they could move out of the townhouse and rent it to someone else.
“If you want to protect yourself from the traps of others, you have to have a game of your own.” Donald told Kelly, “No matter how many sensors you put in, I’m still your dad.”