School of Engineering » News: ABSPIE recent initiatives (tag [accidental fall prediction])

Public datasets of human balance could enable a consensus on the optimal methods for assessing balance and fall risk

Mon, 11 Mar 2019 10:30:00 GMT

Balance impairment and falls are not uncommon in later life. One in three individuals aged 65 and over experiences an accidental fall every year, with head injuries and hip fractures among the most severe consequences. Accordingly, several methods and techniques for assessing balance and fall risk have been developed. Posturography is probably the most common technique and entails the measurement of the body’s centre of mass (CoM) or the centre of pressure (CoP) displacements during standing.

An issue arises when researchers propose and compare new methods of posturography data analysis from different subjects across centres. These data are usually collected following different protocols. Moreover, there are also differences in the algorithms to process and characterise the data. This heterogeneity sometimes generates conflicting findings, most likely produced by a sizeable between-study variability and a low statistical power (i.e. small sample size). As a result, there is still a lack of consensus on the best methods to analyse posturography data in order to extract meaningful information about the subject's balance and fall risk.

Fall risk assessment in older adults? The order could be in the chaos…

Thu, 13 Dec 2018 12:01:33 GMT

· The entropy of Center of Pressure sway can reveal the risk of falling

· Older adults at high risk of falling present more entropic body oscillations, as reflected by CoP sway

· Young subjects and senior adult at lower risk of falling have a much more entropic sway of

Human balance is the result of a dynamic equilibrium. Dynamic, in opposition to static, means that we stand in a vertical position, because we keep balancing opposite forces. If we move our chest forward, with the toes we push on the floor, to bring our chest back avoiding falling. So our standing is not static, but we sway around an ideal centre positioned between our feet. This all happen autonomously, without us paying attention to our postural control.

However, our capability to control posture and balance changes along life. This change can be measured to identify critical variations, which may reveal a higher risk of falling in later life. Accurate detection of these changes can be used to better target interventions aiming to mitigate the risk of falling.

“Well, if it is as easy as it sounds, why this was not done before? In my opinion, the answer is that we were looking in the wrong direction. Previous studies investigated changes in our balance control using measures of order (e.g., stats, periodicity), while we have been looking into the non-linear behaviour of body sway, measuring its entropy. Order change with age, but entropy chance catastrophically in older citizen at higher risk of falling”.

The study recently published by Luis Montesinos and Rossana Castaldo from the applied biomedical signal processing and intelligent eHealth Lab directed by Leandro Pecchia, demonstrated that it is possible to reveal the differences in body sway between older adults and older adult at a higher risk of falling, as determined from their clinical history. These findings represent a significant contribution to the development of improved fall-risk assessment tools in geriatric populations.

L. Montesinos: “With this study, we were not aiming to create new methods for signal analysis. Instead, we were interested in learning how existing methods can be used to identify and understand differences in balance control between older adults at lower and higher risk of falling. In the same way a radio needs to be tuned to pick the station of our choice, the methods we applied require some ‘fine-tuning’ in order to pick differences in body sway between different populations. Our study provided us with interesting insights in this respect, which we want to share with researchers and clinicians in our scientific community and beyond.”

The results of the study were recently published in the Journal of NeuroEngineering and Rehabilitation, the leading academic publication in its subject area of rehabilitation medicine according to Scopus. The article can be accessed here: https://rdcu.be/bdihg

Falls are more likely when you’ve had a bad night’s sleep

Mon, 10 Dec 2018 18:16:00 GMT

Just one night of disrupted sleep means you are less capable to control posture and balance the day after
A single bad night's sleep decreases your chance of controlling posture according to researchers at the University of Warwick, who have used state of the art sensors to monitor sleep and balance
Implications could be that elderly people who have had a bad night's sleep are the most at risk of a fall
Innovative solutions of how to prevent imminent falls can now by researched

Disturbances during sleep decreases capability to control posture and balance according to researchers from the School of Engineering and Warwick Medical School at the University of Warwick who have an article published today in Scientific Reports (www.nature.com/articles/s41598-018-36053-4)

This is the first study demonstrating the relationship between day-to-day variations in sleep quality and the reduced capability to control posture and balance, and it could pave the way to new interventions to prevent falls in later life, should the results be confirmed by other studies on older adults.

The research shows that fragmented and disrupted sleep leads to acute balance deficit.

The study was conducted by the School of Engineering in collaboration Warwick Medical School at the University of Warwick.

A sample of healthy adults underwent sleep and balance assessment over two consecutive days, in order to determine the links between day-to-day variations in sleep quality and balance.

State-of-the-art wearable sensors available at the School were used for in-home sleep monitoring and lab-based balance testing. These findings are relevant to pave the way to the design of fall prevention programs in populations and settings where normal sleep is frequently disrupted, such as older people and hospital wards.

Dr Leandro Pecchia, team leader of the research from the School of Engineering at the University of Warwick says:

“We all have direct experience of this. When we do not sleep well, we may feel a little dizzy and our capability to control our posture and balance is somehow diminished. When we are fit and in good health, our body is able to adapt and we develop a strategy to keep our balance safe, avoiding falls and incidents. This ability is reduced with ageing or when there are other concomitant conditions that may compromise our ability to adapt.”

Prof Francesco Cappuccio, Head of the Sleep, Health & Society programme at the University of Warwick’s medical school, explains:

“The results obtained in healthy normal volunteers are surprising, given the ability at younger ages to compensate for such acute and short-lived sleep disruptions. We would expect more dramatic effects when these experiments be replicated in older people, whose vulnerability to sleep disruption, postural hypotension and risk of falls is much greater”.

Dr Leandro Pecchia continues:

“These results could contribute to the understanding of in-hospital falls. Hospitalised older patients find themselves in a frail condition, sleeping in an unfamiliar environment, with unusual nocturnal light and noises from other patients and nurses, and perhaps being administered more than one drug. Waking-up to go to the toilet can be more challenging than we can imagine. Having a nurse for each bed is not practical in the modern NHS and not well accepted by many older people. We need to learn how to use available technology to detect early the changes in sleep so that we can design personalised interventions that may avoid falls in the next day. One of the problems in fall prevention is that we know a frail subject will fall, but it is very difficult to predict when. Our study is first step towards finding a solution.”

The paper, Day-to-day variations in sleep quality effect standing balance in healthy adults, is published by Scientific Reports.

UK and international news outlets (e.g. the Daily Mail) have received fairly well our paper, which today is in the top 5% of all articles of a similar age based on the online attention it has received.

The study on fall prediction in hypertensive patients via short-term HRV Analysis was awarded the William James Award 2018

Mon, 17 Sep 2018 10:21:00 GMT

Dr Rossana Castaldo, recently awarded her PhD in biomedical engineering, has been awarded the William James Award 2018 by the Institute of Engineering and Technology for her work on fall prediction in hypertensive patients via short-term Heart Rate Variability Analysis recently published on IEEE journal of biomedical and health informatics.

Our research was showcased in the European Medical and Biological Engineering Conference 2017

Mon, 26 Jun 2017 10:42:45 GMT

Recent research results from our lab were showcased in the European Medical and Biological Engineering Conference 2017 (EMBEC’17), which took place from 11^th to 15^th June in Tampere, Finland.

Video: Dr Pecchia invited talk: "HTA of Medical Devices in LMICs"

[media previewImage=https://www.youtube.com/watch?v=2CAzHrQ_wE0 title='HTA in LMICs']https://www.youtube.com/watch?v=2CAzHrQ_wE0[/media]

IEEE JBHI paper "Fall prediction in hypertensive patients via short-term HRV Analysis"

Tue, 29 Mar 2016 09:29:27 GMT

The first paper proving an association between depressed HRV and risk of falling was published on IEEE Journal of Biomedical and Health Informatics in March 2016.

Enrolling 150 subjects, we trained and tested an automatic classifier basing on Multinomial Naïve Bayes enabled to predict first-time fallers. This achieved sensitivity, specificity and accuracy rates of 72%, 61%, 68% respectively.

This was the first sutdy proving this association.