Load cells and dementia: detection, and monitoring in the home
Dementia affects over 850,000 people in the UK, and 42,000 of them are aged under 65. It’s a disease that is often hard to first diagnose, and as it progresses, involves major changes in lifestyle and care requirements.
Dementia is not a natural part of ageing. It a disease of the brain and can be of varying types, such as Alzheimer’s disease, vascular dementia or frontotemporal dementia.
Early diagnosis
One of the main issues with dementia is early diagnosis, and how to determine the degree of progression. One of the major tests currently used includes analysis of levels of physical activity and cognitive functioning. Simple tests such as hand motor function studies help differentiate between age-related decline, mild cognitive impairment and Alzheimer’s.
Keogh et al (1) used load cells to measure the force of a three finger press to help assess the patient’s motor function. Equally, load cells have been used to detect bite force measurement in dementia patients by a team at the University of Amsterdam. (citation)
Load cells can also be used to detect loss of balance-keeping ability. Older people with balance problems are more likely to fall, which can have serious consequences for their subsequent health and mobility. Patients with dementia are more likely to have balance issues. A force platform helps researchers calculate each person’s centre of pressure (COP) and measuring their postural responses to moving visual stimuli. (3)
Ongoing care and support
Load cells can play an important part in allowing dementia patients a degree of independent living. Load cells can be used to monitor patients in their own homes and detect changes in weight, location, gait and movement.
Load cell fitted beds can check a person’s weight, track how long they are in bed, and reassure carers and relations. Some researchers have also used it to monitor breathing, and heart rate too. (4)
A group of Japanese engineers suggested a design for a smart carpet that “employs sensing technology to automatically and unobtrusively monitor a person, detect fall and alert the caregiver by his phone or PC.” (2)
Future uses of load cells
Here at Richmond Industries, we are quite convinced that load cells can play a larger part in the care of dementia patients in their own home and community – we just need to work out how!
We were recently inspired by the use of load cells to map an individual’s sitting posture and its potential use in car security (see last blog). Perhaps that same technology could detect which patient was sitting in which chair in a care community, and help staff detect subtle changes in weight, anxiety levels of sitting times that otherwise might go unnoticed.
Our growing population of seniors
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We’re all going to need to think of new ways to accommodate and care for an increasingly-aged population. In their latest overview of the UK population, The Office for National Statistics stated that:
This may not seem too many now, but due to falling birth rates and people living longer, that figure is set to rise to around 25% of the population aged over 65 by the year 2036. So, we’re always delighted to help researchers, specialists, health workers, medical faculties and colleges, and practitioners build new, smart solutions for all aspects of senior health and senior care. if you have an idea, and think load cells might help it come to fruition, call us. We can design bespoke load cells and systems incorporating wireless technology for remote data analysis.
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NOTES:
(1) Assessment of tri-digit finger-pinch force by XTra 250 N S-beam load cell transducer and BC 302 117.6 N
(2) A Smart Carpet Design for Monitoring People with Dementia https://link.springer.com/chapter/10.1007/978-3-319-08422-0_92_
(3) Púčik, Jozef et al. “Assessment of Visual Reliance in Balance Control: An Inexpensive Extension of the Static Posturography.” Journal of Medical Engineering 2014 (2014): 248316. PMC. Web. 10 Aug. 2017.
and
Measuring Center of Pressure Signals to Quantify Human Balance Using Multivariate Multiscale Entropy by Designing a Force Platform Cheng-Wei Huang 1 , Pei-Der Sue 1 , Maysam F. Abbod 2 , Bernard C. Jiang 3,4 and Jiann-Shing Shieh 1,4,*
Sensors 2013, 13, 10151-10166; doi:10.3390/s130810151 www.mdpi.com/journal/sensors
(4) Conf Proc IEEE Eng Med Biol Soc. 2009;2009:3921-4. doi: 10.1109/IEMBS.2009.5333548.
Classification of breathing events using load cells under the bed.
Beattie ZT1, Hagen CC, Pavel M, Hayes TL.
Oregon Health & Science University, Portland, 97239, USA. beattiez@bme.ogi.edu
