Over the last three decades, the pervasiveness of engineering communication systems, enabled by the development of cheap sensing and computation capabilities, lightweight battery storage and low power actuation systems, has exploded. Concurrently, advances in health care and medicines have and will continue to lead to populations with ageing demographics throughout the industrialised world.
One impact is that the current generation of retirees will live longer and is arguably the first to have grown up with communication and automation technologies as an integral part of everyday life. As a consequence, there are significant opportunities to develop assistive technologies based around automation systems that provide both better quality of life and lower medical costs as user acceptance of the developed technologies will likely be high. Of critical importance is the engagement with the likely users during the development process to ensure that interfaces and social aspects are properly identified. Of particular relevance is the need to avoid overly intrusive approaches, by capitalizing on the embedded nature of suitable technology, and to undertake co-design with the target groups.
The opportunities for automation and ICT technologies then range from non-intrusive detection of incidents, subsequent intervention through partial or potentially complete mitigation of damage through appropriate actions, to assistance in recovery from incidents through appropriate rehabilitation.
As an illustration of the potential benefits of seamless integration of automation, (and one of many that could be highlighted) we can consider falls in the elderly. These represent by far the most common preventable incident with serious consequence for over 65s, and account for a clear majority of hospitalisations in this age group.
From a detection standpoint, there is an opportunity to leverage smartphone uptake (recent surveys have indicated the vast majority of the elderly today own smart phones). The integration of multiple sensors into phones has been already exploited by a number of apps for background fall detection. In essence, these use relatively simple algorithms with thresholds set on acceleration measurements from the inertial measurement units integrated in the phones to trigger the detection of an event. With the introduction of smart watches carrying their own sensors false classification rates will be lowered, as it is easier to prevent false classifications if sensor position is known to be constant with respect to the user’s body.
Naturally, the detection of a potentially injurious event should be coupled with the ability to mitigate the damage. Already in the existing applications, detection of a potential fall via the phone is used to trigger an alert sent to a designated person(s) along with GPS data describing the wearer’s location, typically with a short delay after a fall is detected, where the owner has the opportunity to correct for a false positive classification. Smart phones can also automatically undertake a tiered call response cycle under these conditions, from family, to emergency services.
One of the most serious consequences of falls amongst the elderly is fracture of the femoral head – a more common occurrence as bone density and reaction time of the person (which would aid in in situ fall mitigation) are typically both diminished with age. Furthermore, the complications associated with the surgical procedure for femoral repair lead to significantly increased mortality risk in the elderly. Mitigating the effect of a fall through cushioning the femur in at-risk areas is possible through passive protection, however active devices operating on an air-bag principle activated on fall detection through smart sensing and classification may provide a less intrusive system with better damage mitigation.
Of even greater potential than mitigating a fall is the design and development of devices that can prevent it. Such a system requires early detection before action is taken, thereby relying on more sophisticated sensor feedback and smarter integration with the wearer’s natural actuation capability, so as to provide assistance when required. Already there are commercial prototype systems such as the Hybrid Assistive Limb (HAL) developed by Cyberdyne (no not (yet) the Terminator company!) aiming to do so, which rely on conventional robotic architectures to provide functionality.
Usability will only increase as the man-machine interface is continually refined. Assistive technologies include mechatronic aids, which can assist rather than entirely prevent falls: a lightweight mechanical assistive support device could achieve this, as an intelligent reconceptualisation of the once familiar polio leg braces. However the advent of wearable sensors and soft robotics offers perhaps greater potential due to reduced weight and subsequent reduced on-board power requirements, as demonstrated in prototype systems such as those under development at various research institutes.
Finally, bio-mechatronics offers great potential in targeting rehabilitation strategies towards individual patients. The opportunities include using available sensing technologies to record real world activity, which can be interpreted by clinicians to gauge and improve recovery. Assistive therapeutic aids which initially enhance patient capability through EMG feedback and transition across to systems that retrain or strengthen muscles, thereby reducing the probability of further injurious events. Such approaches may partially alleviate the need for physiotherapy to be conducted wholly onsite, thereby reducing treatment costs and also improving recovery rates.
So while medical and health sciences can claim some responsibility for creating the (nice) problem of an increasing ageing segment of the population, it is perhaps engineering and automation technologies that are going to play a major role in assisting that population to continue to live active and fulfilling lives. It is, however, critical that the age groups concerned play an active participatory and responsible role in the codesign of devices and automation being created for their benefit.
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Article provided by: Prof Chris Manzie Department of Mechanical Engineering University of Melbourne IFAC TC 4.2 (Mechatronic Systems) and 7.1 (Automotive Control)