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AI and sensor data solutions that monitor with nuance to inform care

Long-term care communities can use Artificial Intelligence (AI) and sensor data from firms for incident alerting or for prediction and fall avoidance. Smart combining sensors with data about individuals that have a history of falls, AI tools can detect bed, chair, and room exits which require immediate response.

Pace of tech advancement is even faster than we think...

AI and sensor data to monitor and inform care

There’s no doubt that technology and tools using machine learning, AI and sensors data and more have quickly started to transform the way Independent Living (IL) and Aged Care facilities operate and how seniors are cared for. But one expert says digital care could be advancing even faster than most professionals originally thought.

Independent Living (IL), Aged Care and healthcare in general, are some of the last industries to get digitised, even though things like fax machines are still being used to share information throughout the industry, Dr. Daniel Kraft said (1), founder of Digital.Health and NextMed Health and general partner at Continuum Health Ventures to MobiHealthNews. People are underestimating how quickly things are moving in the digital health field, particularly in terms of AI and ChatGPT.

He also noted that few are fully embracing the digital side of healthcare, and IL and other aged care professionals need to start integrating digital into their workflows more or risk missing out on opportunities for innovation and improving care.

Quickly advancing digital tools, including wearables can monitor with nuance, help detect disease, inform care teams and improve treatments. Those include drug prescriptions and devices needed in treating clients, letting care providers be proactive in care rather than reactive, as many are currently. In terms of generative AI, he envisions a “health bubble” around each individual that talks to them in their language, based on age and culture.

For IL and aged care, using AI to predict diseases and falls is definitely on the horizon for improving care.

AI and sensor data solution examples that monitor with nuance

Traditionally, healthy older adults have only been considered a fall risk after they experience their first fall, so they are considered not a fall risk until it is too late. Several Smart Care companies dedicate himself to preventing the same thing from happening to other families by developing artificial intelligence (AI) technology for early fall-risk detection and prevention. The solutions can derive patterns & alerts that inform care teams.

We compared 4 Smart care solutions like EarlySense , Sleepsense, MDsense for incident alerting or VirtuSense for prediction and fall avoidance.

Traditional alarms operate in black and white. The client triggers the alarm by shifting weight or crossing a sensor boundary, without any context for where the patient actually is. With AI, monitoring can be done with nuance. The AI is trained on massive quantities of data so natural movements like rolling over or reaching across the bed won’t trigger an alarm.

On average, organisations have seen a 74 per cent reduction in falls with injury when using these solutions (2). Clinicians have seen huge improvements in older adult mobility, patient safety, and data-driven care.


Essence Smartcare MDsense, uses an advanced fall detection algorithm with state-of-the-art technology, this wireless fall sensor does not require the resident to wear any detection device. The MDsense can detect a resident’s fall regardless of whether the room is brightly lit or completely dark.


Hill-Rom EarlySense, launches a new generation of hospital beds equipped with heart and respiratory rate sensors. Using EarlySense technology, Centrella Smart+ Beds continuously monitor patients’ vital signs and alerts nurses if a change is detected. EarlySense has been shown to help lower “code blue”-related mortality by 83% and cardiac arrests by 86% (3).


Toch Sleepsense, a solution with similar features as Earlysense but much cheaper, gives care providers bed and health emergency alerts, while providing vital sleep reports and analysis to support actions for improving quality of sleep.

Sleepsense a non-wearable bed sensor and sleep tracker that allows caregivers to monitor a senior’s safety and quality of sleep in real time. Using high-precision sensors and our algorithm technology, the palm-size device is placed under one wheel or leg of the bed. Toch Sleepsense is uniquely designed to detect body movement and vital signs no matter where the sleeper is positioned.


VirtuSense VSTAlert uses in-room sensors to monitor a client's intention to exit their bed and proactively alert care staff.

The LIDAR sensor is mounted across from a patient’s bed and scans 30 times a second. From this data, the AI-based sensor can recognize patterns of movement that indicate an intention to exit the bed. The system then alerts care staff and instructs the client or patient to wait for assistance.

Actually predicting or only detecting falls?

Some of these products are already in use on several Australian care providers sites and have demonstrated a reduced need for frequent in-person checks, reducing resident sleep interruptions and enabling staff to focus on residents who truly require assistance.

Even though they still provide a high number of false positives, the effectiveness of these technologies predicting falls is rapidly increasing!!

AI as a service - to inform care and enable better team responses

Comparing sleepSense, MDsense and VirtuSense’s fall prevention solutions with current bed exit alarms demonstrates how far technology has come.

Toch Sleepsense alerts caregivers in real time when a senior is out of bed, has not returned to bed or may be experiencing a health emergency while in bed. Additionally, sleep quality reports and analysis provides never-before available evidence-based information that can be used in care and medication planning to improve sleep quality and in turn improve quality of life for seniors.

The MDsense is the perfect fall sensor for any Home, IL or retirement facility. The solution can be installed in all the living spaces including bathrooms, to detect falls without the need for wearable fall detection pendants or other active alerting devices.

VSTAlert greatly reduces false alarms and allows patients to be comfortable and unrestrained while maintaining their safety.

The future of AI and older adults

“When people can’t describe their own situation, they need tech to help. Sensors and AI can assist with automated check-in tools that are capable of virtual rounding.”

Amid concerns around the aging population, adopting these long-term, sustainable solutions will ensure care providers are able to cope not only with the demands and pressures of today, but are also in the best possible position to handle what is to come in the future.

Besides reducing risk for both the client and the care organisation, technologies can also indicate whether and when a client has received a visit from a care worker. Organisations can then reward staff workers who exceed expectations about care delivery and more effectively manage those who do not, as well as provide proactive and personalised information built on data about the individual to help optimise care.

Increasingly AI will be incorporated into (new) home design and built into Wi-Fi, part of appliances and voice-operated (4). Within five years, it is inevitable that the role of this tech revolution in our lives and those of older adults will enable changes in society’s focus, occurring in and across multiple domains.

Hubert van Dalen

Hubert van Dalen is Managing Director of eHomeCare, who advises on technology solutions for the care sector for almost 7 years.

Please leave a comment, and share your experience if they've used these products before, or have questions about them?




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