DOSSIER FALLSKIP

The most innovative and reliable

biomechanical application to evaluate fall

risk in older adults

SCIENTIFIC & TECHNICAL

INFORMATION

Instituto de Biomecánica - IBV Universitat Politècnica de València

Camino de Vera s/n Edificio 9C

+34 96 111 11 70 www.ibv.org

Developed by IBV

fallskip.com

TABLE OF

CONTENTS

01 What is FALLSKIP?

02 Why FALLSKIP?

03 Scientific basis

04 Reliability

05 Bibliography

06 Acknowledgments

07 About IBV

3

01 What is FALLSKIP??

allSkip is a new biomechanical application,

which allows clinicians to evaluate older

adults´ fall risk, attributed to their functional

state. The system uses an Inertial

Measurement Unit integrated in an Android

device, which is responsible to analyse the

biomechanical response when performing a

modified protocol of the Time up Go Test

(TGU).

The test is developed in four consecutive

phases according to the following scheme:

Phase 1. Standing: The measurement begins with the patient standing, facing forward, arms at both sides, for 30 seconds.

Phase 2. Gait: When the device emits a sound, the patient starts walking along a corridor of three meters in a straight line, towards a chair.

Phase 3. Sitting and rising: At the end of the corridor, the patient has to sit and then rise from a chair.

Phase 4. Gait: The patient walks in the opposite direction until he reaches the test starting position

The measuring device, located in the patient's lower back, records the accelerations generated by the patient's movement throughout the test. From the acceleration measured, the system segments the phases of the test and sets the parameters to calculate the biomechanical variables associated with the risk of falling:

Balance assessment by analyzing the displacements of the center of mass during the standing phase.

Gait assessment by analyzing the displacement of the center of mass and the duration of the gait phase.

Assessment of lower limb strength the by analyzing the power to perform the movement.

Evaluation of the reaction time to an auditory stimulus, in the transition between the first and second phase of the test.

01 What is FALLSKIP?

F

6

Gait

3 meters Starting point 30 seg

Open Eyes Romberg Sit & rising

The FallSkip application assesses the overall

risk of falling by combining the result of the

biomechanical test with the main risk factors,

age, gender and patient history of falls. The fall

risk result is available immediately after the

test, which is accompanied by a

comprehensive evaluation of the main

biomechanical parameters related to falls; By

this way, clinicians are assisted during the

diagnosis phase, making easier the decision

making process.

The assessment lasts, including the

instrumentation of the patient and the

performance of the test, approximately two

minute. This device has been designed to be

used by healthcare personnel in the clinical

setting, where objectivity and time-saving

provide a great added value in clinical

protocols.

Besides, the application include a set of belts

to facilitate the correct positioning of the

device (between iliac crests), a pair of

headphones to amplify the acoustic signal in

case of hearing impairments, and a universal

battery charger.

01 What is FALLSKIP?

7

8

02 Why FALLSKIP??

One out of three older adults falls at least once

a year, which is one of the major geriatric

syndromes and the second world cause of

accidental or unintentional death (WHO,

2016; Samantha Turner, Rupert Kisser, & Wim

Rogmans, 2015).

A fall usually implies a deterioration in the

autonomy of elderly people, which reduces

their quality of life and that of their social

environment. The consequences range from

clinical problems such as fractures or sprains

to the fear of falling syndrome, which involves

an increase in the fragility of the older person

and the onset of functional disability (Olmos

Zapata, 2012).

According to da Silva Gama, Conesa, &

Ferreira, (2008), falls affect approximately

16.5% of elderly people in Spain. The

psychosocial and assistance consequences, as

well as the fear of falling syndrome, affect

between 64% and 44.7%; in addition,

between 9.7% and 19% of the falls result in

hospital admission of the elderly person.

There are several methods to assess the

functional capacity and the risk of falling;

however, they show some limitations because

not all of them are repeatable and they are

usually based on subjective criteria.

One of the methods with more scientific

evidence is the Physiological Profile

Assessment, (Lord, Menz, & Tiedemann,

2003); however, it has the disadvantage of

being too expensive in terms of time for daily

use clinical practice. In order to provide a more

versatile solution adapted to the needs of

healthcare professionals, the IBV has

developed a new biomechanical application,

FallSkip: assessment of the risk of falling,

which has been possible thanks to more than

40 years of experience that the IBV has in the

field of research and innovation in health

technology and elderly people.

FallSkip allows the user to measure in less than

one minute the risk of falling of a person based

on his or her functional state. To do this, the

system analyzes the biomechanical response

of the patient when performing a modified

protocol of the "Time Up & Go" (TUG) test,

which makes it especially appropriate to cover

the needs of primary, specialized and social

care professionals.

The aging of the world population is an obvious reality nowadays. The increase in the

population over 65 implies an increase in the number of falls.

According to the WHO, prevention strategies to be adopted by healthcare systems should

address the identification of risk factors; in fact, research shows that effective preventive

measures reduce the risk of frequent falling in seniors by 30 to 40%

02 Why FALLSKIP?

10

03 Scientific basis

The methodology followed by FALLSKIP is

based on the application of an adapted version

of the “Time up Go” Test (TUG), which has

been cited in multiple clinical trials [11, 15] as

a reliable and cost-effective method for

assessing general functional state. Besides,

these studies have demonstrated the

efficiency of this test for obtaining some

parameters related with human gait, balance,

motor control or muscle strength. In fact,

according to Herman and cols. [3], the TUG

test is a widespread tool that allows

researchers to obtain reproducible results in

older adults, with an ICC=0.99.

Despite its clinical usefulness, there are a

significant number of scientific proofs, which

claim that collecting how long the TUG test

lasts, as a unique objective factor, is an

inconsistent way to classify between people

with and without fall risk. This is why

researchers complement this data with other

biomechanical variables, which are globally

accepted due to their discriminatory capability

between fallers and non-fallers [16, 17, 18].

For this reason, in an effort to improve the

practical applicability of the test as a method

of evaluation older adults´ fall risk, researchers

have been recently using new wearable

measurement instruments based on inertial

movement units (IMU) [4]. These sensors

allow professionals to evaluate different

biomechanical variables throughout the test´s

milestones, providing quantitative data like

temporal, kinetic and kinematic parameters.

There are multiple evidences about the

applicability of IMU sensors for getting TUG´s

quantitative parameters [17, 21]. Higashi and

cols. [4] published some examples in the

evaluation of hemiplegic patients with gait

impairments. Similarly, Weiss and cols. [21]

used this technology to define an

instrumented version of TUG test in patients

with Parkinson. Other evidences are found in

the studies carried out by Martinez-Ramirez

[10], who describe a satisfactory method to

assess balance alterations.

Regarding the biomechanical variables used by

FallSkip it is important to remark the great

number of papers that justify their high

statistical correlation with fall risk. In that way,

Hausdorff and cols. [2] conclude that there is

a significant correlation between

biomechanical parameters, which describe gait

variability, and fall risk.

03 Scientific basis

11

Actually, the specialized literature

demonstrates that the more step variability

the higher risk of falling. Following this

approach, there are other studies, like those

published by Mancini or Topper and cols. [9,

20], that prove the tighten relationship

between the biomechanical parameters

related with balance functionality and fall risk;

the larger centre of masses oscillation the

higher danger of falling.

Similarly to the aforementioned studies, the

results presented by Perry and cols. [14]

support the need for identifying those

biomechanical parameters closely related with

lower limb strength; the reason lies in the high

correlation between those variables and older

adults´ fall risk. In that sense, McCarthy, Yuan-

Yang and cols. [12, 22] remark the usefulness

of the sit-to-stand protocol to evaluate

clinically the functionality level of lower limbs

in terms of muscle strength and power.

Finally, Mirelman, in his study published in

2012 [13], discusses about the influence of a

diminished reaction time over the fall risk. In

the same direction, the studies carried out by

Laessoe and Lord [5, 6] reach the same

conclusion (the longer muscular activation

time, the higher fall risk).

03 Scientific basis

12

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04 Reliability

The Physiological Profile Assessment (PPA) QuickScreen© is considered the current gold

standard [7]. This method, which consist of 5 different independent tests, presents an ICC,

depending on the tests, between 0.55 and 0.85 [7], with a predictive precision between

70 and 75% [8].

In that sense, a study was undertaken by the Institute of Biomechanics (IBV) among a

sample of 65 older adults, who were evaluated, by three independent observers, using PPA

and Fallskip methodology. The correlation obtained between these two methods is -0.65

(p<0.01 bilateral).

In the same experiment, a reliability study of Fallskip methodology was also conducted,

getting a value of the Cronbach's Alpha statistic of 0.97, with an ICC between 0.88 and

0.95. These results prove the high reliability of the protocol and biomechanical model

implemented in Fallskip.

04 Reliability

15

05 Bibliography

1. Cho MD, Scarpace D, Alexander MD. Tests of Stepping as Indicators of Mobility, Balance, and Fall Risk in Balance-Impaired Older Adults Be-long. J Am Geriatr Soc. 2004; 52(7):1168-73

2. Hausdorff JM, Rios DA, Edelberg HK. Gait variability and fall risk in community-living older adults: A 1-year prospective study. Physical Medicine & Rehabilitation. 2001; 82 (8): 1050–1056

3. Herman T, Giladi N, Hausdorff JM. Properties of the ‘timed up and go’ test: more than meets the eye. Gerontology. 2011;57(3):203-10

4. Higashi Y, Yamakoshi K, Fujimoto T, Sekine M, Tamura T. Quantitative evaluation of movement using the timed up-and-go test, IEEE Eng Med Biol. 2008; 27 (4)

5. Laessoe U, Hoeck HC, Simonsen O, Sinkjaer T, Voigt M. Fall risk in an active elderly population – can it be assessed? Journal of Negative Results in BioMedicine2007; 6:2

6. Lord SR, Dayhew J. Visual Risk Factors for Falls in Older People. J Am Geriatr Soc. 2001; 49(5):508-15

7. Lord SR, Menz HB, Tiedemann A. A Physiological Profile Approach to Falls Risk Assessment and Prevention. Physical Therapy, 2003; 83 (3): 237–252

8. Lord, S. R., Ward, J. A., Williams, P., & Anstey, K. J. (1994). Physiological factors associated with falls in older community‐dwelling women. Journal of the American Geriatrics Society, 42(10), 1110-1117.

9. Mancini M, Horak FB. The relevance of clinical balance assessment tools to differentiate balance deficits. Eur J Phys Rehabil Med. 2010; 46(2): 239–248

10. Martínez-Ramírez A, Lecumberri P, Gómez M, Rodriguez-Mañas L, García FJ, Izquierdo M. Frailty assessment based on wavelet analysis during quiet standing balance test, J Biomech. 2011; 44: 2213-20

11. Mathias S, Nayak U, Isaacs B. Balance in elderly patients: the ‘get-up and go’ test, Arch Phys Med Rehabil. 1986; 67: 387-9

12. McCarthy EK, Horvat MA, Holtsberg PA, Wisenbaker JM. Repeated Chair Stands as a Measure of Lower Limb Strength in Sexagenarian Women. J Gerontol A Biol Sci Med Sci. 2004;59(11):1207-12

13. Mirelman A, Herman T, Brozgol M, Dorfman M, Sprecher E. Executive Function and Falls in Older Adults: New Findings from a Five-Year Prospective Study Link Fall Risk to Cognition. PLOS ONE 2012; 7(6)

05 Bibliography

17

14. Perry MC, CarvilleI SF, Smith CH, Rutherford OM, Newham DJ. Strength, power output and symmetry of leg muscles: effect of age and history of falling. European Journal of Applied Physiology. 2007; 100 (5): 553–561

15. Podsiadlo D, Richardson S. The timed ‘Up & Go’: a test of basic functional mobility for frail elderly persons, J Am Geriatr Soc. 1991; 39: 142-8

16. Sabatini AM, Martelloni C, Scapellato S, Cavallo F. Assessment of walking features from foot inertial sensing, IEEE Trans Biomed Eng., 2005; 52: 486-94

17. Salarian A, Horak FB, Zampieri C, Carlson-Kuhta P, Nutt JG, Aminian K. iTUG, a sensitive and reliable measure of mobility, IEEE Trans Neural Syst Rehabil Eng. 2010; 18: 303-10

18. Savva GM, Donoghue OA, Horgan F, O’Regan C, Cronin H, Kenny RA. Using timed up-and-go to identify frail members of the older population. J Gerontol A: Biol Sci Med Sci. 2013; 68: 441-6

19. Skelton DA, Kennedy J, Rutherford OM. Explosive power and asymmetry in leg muscle function in frequent fallers and non‐fallers aged over 65 Dawn. Age Ageing. 2002 Mar;31(2):119-25

20. opper AK, Maki BE, Holliday PJ. Are Activity-Based Assessments of Balance and Gait in the Elderly Predictive of Risk of Falling and/or Type of Fall? Journal of American Geriatrics Society. 1993; 41 (5): 479–487

21. Weiss A, Herman T, Plotnik M, et al. Can an accelerometer enhance the utility of the Timed Up & Go test when evaluating patients with Parkinson’s disease? Med Eng Phys. 2010; 32: 119-25

22. Yuan-YangChengabShun-HwaWeicPo-YinChenc1Mei-WunTsaicI.-ChungChengcDing-HaoLiubdChung-LanKao. Can sit-to-stand lower limb muscle power predict fall status? Gait & Posture. 2014; 40 (3): 403-407

18

We thank the following entities for their support and interest in the IBV research line on

the assessment of the risk of falling in the elderly: Business Association of Retirement

Homes and Services for Dependent People of the Valencian Community (AERTE), Physical

Medicine and Rehabilitation Service of La Fe University and Polytechnic Hospital in

Valencia, Valencian Society of General Practitioners, Valencian Society of Physical

Medicine and Rehabilitation, La Ribera Hospital, Elderly Department of Mislata Town Hall

and Gestión Sanitaria del Mediterraneo S.L.

06 Acknowledgments

21

The Instituto de Biomecánica (IBV) is a technological centre that studies the behaviour of

the human body and its interaction with products, environments and services. With a clear

international projection, the IBV set up in 1994 thanks to the support of the Valencian

Entrepreneurial Competitiveness Institute (IVACE), the Polytechnic University of Valencia

(UPV) and other public and private stakeholders.

The IBV promotes people’s well-being through the combination of knowledge in areas such

as biomechanics, ergonomics and emotional engineering, and its application to diverse

sectors.

The IBV is core partner of the EIT-Health, which leverages the expertise of more than 140

leading organisations spanning key areas of healthcare, such as pharma, medtech, payers,

research institutions and universities https://www.eithealth.eu/

07 About IBV