The ‘Holy Grail’ of fall detection is, of course, fall prevention. The CDC statistics for the US are well known: One in four Americans aged 65+ falls each year. Every 19 minutes, an older adult dies from a fall. Falls are the leading cause of fatal injury and the most common cause of nonfatal trauma-related hospital admissions among older adults–2.8 million injuries treated in emergency departments annually, including over 800,000 hospitalizations and more than 27,000 deaths. In 2014, the total cost of fall injuries was $31 billion. In the UK, AgeUK‘s stats are that falls represent the most frequent and serious type of accident in people aged 65 and over, the main cause of disability and the leading cause of death from injury among those aged 75+.
The technology ‘cures’ as noted in this NextAvenue/Forbes article centers around predicting if and when a person will fall.
- The ‘overall’ approach, which is constant monitoring of ADLs through activity sensing and modeling/machine learning to detect early signs of decline or health change. Companies in this area are Care Innovations’ QuietCare (sensor arrays) and CarePredict (wrist worn).
- Gait detection. Relatively small changes in gait and walking speed are an accurate, fast, and straightforward indicator of fall risk. Ten years of research performed at TigerPlace in Missouri showed that people whose gait slowed by 5 centimeters per second within a week had an 86% probability of falling during the next three weeks. Shortening of stride had a 50 percent probability of fall within three weeks.
- Read the brain. Research at Albert Einstein School of Medicine in NYC indicates that in otherwise high-functioning older people, high levels of frontal brain activity while walking and talking can predict higher long term fall risk, up to 32 percent.
- Balance impairment. Tests using VR to simulate falling in healthy subjects and tracking their muscular response also could be used to roadmap a person’s balance impairments and future fall risk–along with training and targeted physical rehabilitation.
The Netherlands has taken this last point and gone ‘low tech’ with physical training courses that teach older adults both not to fall and to fall correctly if they do. Students negotiate obstacle courses and uneven surfaces, then learn to fall properly on thick inflated mats. Many of those attending use walkers or canes, but complete the courses which reduce the fear of falling or getting up–and provide both fun and socialization. The courses have become popular enough that they are government rated with insurance often defraying the cost. New York Times
[grow_thumb image=”http://telecareaware.com/wp-content/uploads/2016/03/fall.png” thumb_width=”150″ /]Carnegie-Mellon University-College of Engineering
recently conducted a survey of 1,900 US adults on care for their aging parents, as background for a project in fall prevention.
- 81 percent are interested in sensor technology to prevent falls, particularly among their aging parents
- 54 percent worry about an elderly parent falling
- 70 percent of this group have this fear at least once a week, if not daily; regardless of whether the parent lives alone or not
Checking in with parents is a ‘top of mind’ anxiety for most of those surveyed, with most taking a team approach:
- 44 percent personally or have a sibling check in on their parent daily; 33 percent check in weekly; 12 percent stop by as needed
- 56 percent have neighbors or staff physically check on their parent daily
Not coincidentally, a team of engineers from Carnegie-Mellon are also researching active sensor technologies that gauge gait stability, dizziness and fatigue to predict and prevent falling–what at a former company we called the ‘Holy Grail’ of fall detection that can keep older adults active and well. No mention though of technology aids for ‘check in’ (see 3rings and also the original notion of QuietCare‘s behavioral telemonitoring.) MedCityNews, Carnegie-Mellon release
[grow_thumb image=”http://telecareaware.com/wp-content/uploads/2013/02/gimlet-eye.jpg” thumb_width=”175″ /]The Gimlet Eye falls outside the box, and is writing this from recovery. Our
companion in curmudgeonliness, Laurie Orlov
, whacks us upside the head with first the good news then the bad. US life expectancy is up: if you are 65 today, on average you will live to 83 (men) and 86 (women), even with the rise in chronic conditions that affect quality of life, such as diabetes and heart disease. But the bad
is that death from falls is also up. This is despite all the systems and gizmos the Digital Health Industry has concocted to detect falls beyond
1970s PERS technology. Once upon a rose-colored Telecare Time we thought we could infer falls purely by sensors detecting lack of activity (the basis of QuietCare, GrandCare, Healthsense,
the late WellAWARE
). Then with accelerometers
, fall detection would be automatic, (more…)
[grow_thumb image=”http://telecareaware.com/wp-content/uploads/2014/04/skinpatch-1-John-Rogers.jpg” thumb_width=”150″ /] From the head researcher (John Rogers at the University of Illinois at Urbana-Champaign) who brought you biodegradable implanted batteries and sensors [TTA 26 March], comes an almost tattoo-like stretchable sensor conforming to the skin which uses off-the-shelf, chip-based electronics for wireless monitoring. It is envisioned for wireless health tracking connecting to smartphones and computers, and for vital monitoring such as ECG and EEG testing, although this Editor would not use the term ‘clinical’ as Gizmodo has done (it is probably at the fairly sound level of an AliveCor.) However the article points out the advantages in long term use–adherence to skin is far more reliable, no dangling pendants or clunky bracelets, and it allows for multiple sensors to be worn comfortably. This type of patch would also be far kinder to the delicate skin of babies and the elderly. For them, it would make consistent long-term telehealth monitoring (e.g. blood pressure, ECG, O2, blood glucose) far easier over time. Perhaps the core of this is the PERS of the future with gait tracking and fall detection. Cost isn’t mentioned, but off the shelf elements undoubtedly are less expensive than custom/bespoke. Published in Science 4 April (abstract and summary; full text requires log in) Also see Editor Charles’ earlier take–maybe Mr. Rogers should speak to him!