A Pilot Study to Detect Balance Impairment in Older Adults Using an Instrumented One-Leg Stance Test.

TL;DR: The findings suggest that the normal one-leg stance test might not be suitable to detect fall risk, and that an instrumented version of the test could provide valuable additional information that could identify risk of falling in older people.

Abstract: The aim of this study was to investigate whether parameters from an instrumented one-leg stance on a force plate test could provide relevant information related to fall risk in older people. Twenty-five community dwelling older people and 25 young subjects performed a one-leg stance while standing on a force plate, with parameters related to transferring weight onto one leg and postural sway in singe-leg stance evaluated. Older participants were classified as being at risk of falling if their performance did not meet one of the previously-established cut-offs for the Five Times Sit-To-Stand and Timed-Up-and-Go tests. Eleven older participants were classified as having a risk of falls. The only significant difference between groups during the weight transfer phase was in the mediolateral displacement, with the fall risk group having less sway than the other groups, signifying a more precautionary approach. With respect to postural sway, both the younger subjects and the no fall risk group stabilised sufficiently to decrease their sway compared to initial values after four and six seconds, respectively. In contrast, the fall risk group was unable to stabilise during the one-leg stance, and continued to sway throughout the 10-sec recording period. These findings suggest that the normal one-leg stance test might not be suitable to detect fall risk. In contrast, an instrumented version of the test could provide valuable additional information that could identify risk of falling in older people.

Summary

INTRODUCTION

• Falls typically occur in around 30% of older adults each year, with up to 20% of these falls resulting in injury, hospitalisation and even death [1, 2].
• Given the healthcare and economic consequences of falls, interventions that decrease the incidence of falls are needed.
• Another widely-used functional screening tool is the One Leg Stance (OLS) test, which requires the person being assessed to stand on one leg for as long as possible [13].
• One reason for this finding could be that the test uses only the time a person can balance on one leg and does not consider any information about the way in which a person maintains balance.
• These studies have used different balance parameters such as time to stabilisation (TTS) [17], the variability of the force developed [18], the amount of centre of pressure (CoP) displacement [19], and the CoP velocity and surface area [20].

Participants

• A group of 25 community-dwelling older people were included based on inclusion criteria of having not fallen in the previous two years, no medical conditions related to an increased fall risk, and not taking any medication known to increase fall risk.
• Participants were asked to step on the force plate, stabilise on two feet then perform the OLS on their preferred leg, with their best time taken as their OLS performance.
• Data was collected at 1000 Hz using Bertec’s Digital Acquire software (Version 4.0).
• Statistical analyses were performed using SPSS version 25 (IBM Corp, Armonk, New York, USA).
• Owing to the post-hoc nature of this analysis, Bonferroni adjustments were made to p values for statistical significance.

RESULTS

• Bootstrapped means and confidence limits for the performance of the two groups of non-falling older participants and the fallers in the three screening tests are shown in Table 1.
• There was no difference between fallers and non-fallers for TUG performance (r=0.14), however fallers were significantly worse at the 5STS test (r=0.53), which corresponds to a large effect.
• The number of older non-fallers classified as being at risk of falling using the cut-offs for the TUG and 5STS was 11 (44%), with five subjects were classified as being at risk of falls by both tests (20%), and six subjects classified as being at risk of falls by one of the tests (24%).
• Four fallers were classified as having no risk of falling (23.5%), four fallers were classified as having a risk of falling by both tests (23.5%), while nine fallers were classified as being at risk of falls only by the 5STS (53%).

Weight Transfer Phase

• There were no significant differences in the mean durations of the weight transfer phase for the three groups (H=3.195, p=0.202).
• Bootstrapped means and standard deviations of the total CoP displacement for both anteroposterior and mediolateral displacement are shown for all three groups of participants in Figure 3.
• There were no significant differences between the groups for either displacement direction based on the KruskalWallis test (Anteroposterior: H=0.105, p=0.949; Mediolateral: H=2.226, p=0.329).
• There were significant effects of the group for each of the five time periods, as well as for the overall postural sway for the entire 10 seconds of the test.

DISCUSSION

• The findings of this pilot study offer evidence that an instrumented version of the OLS could provide additional information related to fall risk in older people when compared to the standard OLS test.
• The analysis addressed both the weight transfer and the single leg stance phases of the test.
• Thereafter, older non-fallers swayed more than the younger participants, suggesting the difference in sway was due to the ability of the younger subjects to stabilise their posture.
• This means that the findings of the study might not apply to people unable to maintain the OLS for five seconds.
• The instrumented OLS was able to discriminate between fallers and non-fallers based on the amount of sway when standing on one leg, unlike other functional tests.

Disclosure statement

• The authors certify that they have no conflict of interest in the subject matter discussed in this manuscript.
• Ethical approval Ethical approval was granted by the Ethics Committee of the Dr S.N Medical College of Jodhpur (Ethical approval: 1262/6419).
• All participants read an information sheet and gave their informed consent.
• None of the subjects had any known musculoskeletal or neurological disorders nor had fallen in the previous twelve months.

Figures

Table 2. Effect sizes for differences in postural sway

Table 1. Functional screening test results

Figure 4: Range of centre of pressure displacement for older and younger participants. Data are bootstrapped means; error bars are 95% confidence intervals of the means.

Figure 5: Sway area of the OLS for fall risk and no fall risk participants. Data are bootstrapped means; error bars are 95% confidence intervals of the means. *Significant difference from time period 0-2 sec (p<0.05); † Significant difference from young group (p<0.05).

Figure 1. Example of a typical segmentation for the OLS signal using the mediolateral centre of pressure.

Figure 2: Velocity of centre of pressure displacement for older and younger participants. Data are bootstrapped means; error bars are 95% confidence intervals of the means.

Figure 3: Total centre of pressure displacement for older and younger participants. Data are bootstrapped means; error bars are 95% confidence intervals of the means.

Full text

This manuscript version is made available under the CC-BY-NC-ND 4.0 license
http://creativecommons.org/licenses/by-nc-nd/4.0/
The final version of this article is available on the publisher’s website:
https://doi.org/10.1115/1.4046636

1
A pilot study to detect balance impairment in older adults using an
instrumented one-leg stance test
Jennifer N.C. Bassement
1
, Brajesh K. Shukla
2
, Sandeep K. Yadav
2
, Vivek Vijay
2
, Arvind Mathur
3
, David
J. Hewson
4
1. Centre Hospitalier de Valenciennes, France
2. Indian Institute of Technology Jodhpur, Jodhpur, India
3. Asian Centre for Medical Education, Research & Innovation, Jodhpur, India
4. Institute for Health Research, University of Bedfordshire, Luton, United Kingdom
SHORT TITLE
Instrumented OLS detection of balance impairment
FULL ADDRESS FOR CORRESPONDENCE
Professor David Hewson
Institute for Health Research
University of Bedfordshire
University Square
Luton
Bedfordshire LU1 3JU
Phone: +44 (0)7525616645
Email: david.hewson@beds.ac.uk
EMAIL ADDRESSES
Dr Jennifer Bassement jennifer.bassement@uphf.fr
Brajesh Shukla shukla.1@iitj.ac.in
Dr Sandeep Yadav sy@iitj.ac.in
Dr Vivek Vijay vivek@iitj.ac.in
Dr Arvind Mathur mathurarvindju@gmail.com
Prof David Hewson david.hewson@beds.ac.uk

2
!

3
ABSTRACT!
The aim of this study was to investigate whether parameters from an instrumented one-leg stance
(OLS) on a force plate could provide relevant information related to fall risk in older people. Forty-two
community dwelling older people including 17 fallers and 25 non-fallers, and 25 young subjects
performed a one-leg stance while standing on a force plate, with parameters related to transferring
weight onto one leg and postural sway in singe-leg stance evaluated. No differences were observed
between older fallers and non-fallers and the younger participants for any of the weight transfer
parameters. The younger participants were able to reduce their postural sway during the OLS test
after the first 0-2 second period, unlike older participants who swayed the same amount throughout
the test. The older fallers swayed significantly more than both non-fallers and younger participants
throughout the 10-seconds of OLS evaluated. When the tests were used to classify older participants
as fallers, the instrumented OLS achieved 100% accuracy, compared to 69.0% classification accuracy
for the five times sit-to-stand test, 61.9% for the standard OLS and 47.6% for the timed-up-and-go
test. These findings suggest that the standard OLS test might not be suitable to detect fall risk. In
contrast, an instrumented version of the OLS could provide valuable additional information that could
identify older fallers. Future work will include a prospective study of the instrumented OLS in a larger
population of older people.
Keywords
Balance, falls, functional screening.

4
INTRODUCTION!
Falls typically occur in around 30% of older adults each year, with up to 20% of these falls resulting in
injury, hospitalisation and even death [1, 2]. Falls place a substantial burden on all countries in terms
of healthcare and economics, with the cost of a fall estimated at US$2000, rising to US$42,000 when
there is a fall-related injury [3]. Given the healthcare and economic consequences of falls,
interventions that decrease the incidence of falls are needed. Some studies have reported that
interventions such as strength and balance training, and walking, can decrease both the incidence and
severity of falls [4]. However, it is too costly to provide such interventions for all older people, making
it necessary to identify older people at increased risk of falls, who can then be targeted for fall
prevention. There are many risk factors for falls in older people, including a previous history of falls,
gender, living alone, use of medication, and impaired balance and gait [5-7].
Several different clinical tools have been developed to identify fall risk, including questionnaires such
as STRATIFY [8] and the self-rated fall-risk questionnaire [9] and functional tests such as the Berg
Balance Test [10], Timed Up and Go Test (TUG) test [11], and the Five Times Sit to Stand Test (5STS)
[12]. Another widely-used functional screening tool is the One Leg Stance (OLS) test, which requires
the person being assessed to stand on one leg for as long as possible [13]. The OLS is cost effective,
easy to administer, time efficient and does not require much equipment [7, 14, 15]. However,
although the OLS has been found to be associated with an increased prevalence of fracture, a direct
association with fall risk is not always clear [16]. One reason for this finding could be that the test uses
only the time a person can balance on one leg and does not consider any information about the way
in which a person maintains balance.
Some studies have attempted to extract additional information from the OLS by requiring users to
perform the test while standing on a force plate. These studies have used different balance
parameters such as time to stabilisation (TTS) [17], the variability of the force developed [18], the
amount of centre of pressure (CoP) displacement [19], and the CoP velocity and surface area [20]. In

Frequently asked questions

Q1. What are the contributions in "A pilot study to detect balance impairment in older adults using an instrumented one-leg stance test" ?

In this paper, the authors compared balance parameters extracted from an OLS, including CoP displacement and surface area with the TUG and 5STS screening tests to investigate whether balance parameters during single leg stance could provide relevant information related to fall risk in older people. 

Q2. What future works have the authors mentioned in the paper "A pilot study to detect balance impairment in older adults using an instrumented one-leg stance test" ?

Future work will include prospective fall risk using falls diaries, with a larger participant group that would ideally include some participants who fail the standard OLS test. Future work could also use a lower-cost, portable device such as the Wii Balance Board or the Balance Quality Tester, which is an intelligent bathroom scale that can measure balance remotely. 

Q3. What is the purpose of this study?

The aim of this pilot study is to compare balance parameters extracted from an OLS, including CoP displacement and surface area with the TUG and 5STS screening tests to investigate whether balance parameters during single leg stance could provide relevant information related to fall risk in older people. 

Q4. How many falls occur in older adults each year?

Falls typically occur in around 30% of older adults each year, with up to 20% of these falls resulting in injury, hospitalisation and even death [1, 2]. 

Q5. What are some studies that have reported that can reduce the incidence and severity of falls?

Some studies have reported that interventions such as strength and balance training, and walking, can decrease both the incidence and severity of falls [4]. 

Q6. How was the amount of postural sway calculated?

The amount of postural sway in the OLS was calculated as the surface area of a circle covering 95% of the CoP oscillation (Area) [23], with sway calculated for each 2-second interval across the ten seconds of the OLS retained for analysis. 

Q7. What were the parameters used to quantify the weight transfer phase?

The parameters used to quantify the weight transfer phase, when participants shifted their weight to one leg were the total excursion of the CoP (TOTEX), the mean velocity of the CoP (MVELO), and the range of the CoP (Range) [23]. 

Q8. How many older people were classified as being at risk of falling?

The number of older non-fallers classified as being at risk of falling using the cut-offs for the TUG and 5STS was 11 (44%), with five subjects were classified as being at risk of falls by both tests (20%), and six subjects classified as being at risk of falls by one of the tests (24%). 

Q9. How many fallers were classified as having a risk of falling?

Four fallers were classified as having no risk of falling (23.5%), four fallers were classified as having a risk of falling by both tests (23.5%), while nine fallers were classified as being at risk of falls only by the 5STS (53%). 

Q10. What is the way to measure balance remotely?

Future work could also use a lower-cost, portable device such as the Wii Balance Board or the Balance Quality Tester, which is an intelligent bathroom scale that can measure balance remotely. 

Q11. How was the sway calculated for the three participants?

For the three participants who were unable to achieve a 10-second OLS, missing values for the missing 2-second sway intervals were imputed using multiple linear regression.