AI monitoring


AI monitoring: enabling a holistic approach to resident wellbeing


Thomas Tredinnick, CEO and co-founder of Ally Cares, discusses the revolutionary impact of AI-powered acoustic monitoring systems, which are facilitating a truly holistic vision of care delivery


Technology is playing an increasingly vital role in shaping the quality and effectiveness of care being provided. Among the most transformative advancements is the integration of AI-powered acoustic monitoring systems, which are revolutionising how care is delivered in care homes. These systems not only fill crucial gaps in the current care model but also help complete the care picture by providing a holistic understanding of each resident’s needs.


The importance of a holistic approach in resident care When exploring the context of caring for the elderly, taking a holistic approach refers to considering all aspects of a resident’s wellbeing – physical, emotional, and psychological. Traditional care models rely heavily on


direct staff to resident interactions and observations, requiring carers to detect subtle changes and ask the right questions. However, this approach has inherent limitations. Gaps in knowledge occur due to time


constraints, high resident-to-staff ratios, residents’ privacy needs, and the complexity of individual needs. Research shows that, on average, residents spend some 48 per cent of their time during the day1 and 11 hours at night,2


in their rooms a total of around


19 hours each day where they might be unobserved. Unsurprisingly, care teams can easily miss critical insights when residents are alone, when staff are stretched, or when residents say they are ‘fine’ but are omitting key things simply to not be a burden on the


October 2024 www.thecarehomeenvironment.com


stretched care team. The detection of issues is then delayed and leaves unanswered questions about a resident’s behaviour / wellbeing.


The role of AI monitoring systems is crucial in addressing these gaps. By continuously observing residents when they are alone in their rooms, we can glean vital insights that might otherwise go unnoticed or communicated. These systems can reveal underlying issues, such as increased coughing, restless sleep, movement, agitation, or signs of pain, distress, or discomfort which can be indicative of unrecorded incidents or emerging health problems.


These insights enable care teams to respond more quickly to residents’ needs, providing timely support when residents are distressed or moving unsupervised. They can also flag health changes, like a developing chest infection, and offer valuable context for unexplained issues, such as daytime sleep or weight loss.


The most powerful systems combine movement and sound with advanced AI algorithms


How AI monitoring works AI-powered resident monitoring systems are designed to monitor residents effectively by mimicking the human senses of sight and hearing. Typically, these systems monitor just movement, using infra-red / thermal, pressure matts and – more recently – cameras. But the most powerful systems combine


movement and sound with advanced AI algorithms to analyse the data collected ensuring even the subtlest signs of distress or discomfort are detected. n Movement sensors: these sensors track the physical activity of residents, such as getting in and out of bed, moving around the room, or lack of movement for extended periods. This data can help caregivers understand the resident’s mobility and identify any sudden changes in activity levels, which may indicate potential health issues.


n Acoustic sensors: these sensors detect and capture sounds even when residents are not moving or out of sight from the movement sensors, such as coughing, crying, or calling for help. For example, if a resident is in the corner of their room not moving but audibly in pain, the system can alert staff to provide immediate assistance. Similarly, if a


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