- •Instrumented testing of five physical capability tasks with a single accelerometer.
- •Evaluated on a large cohort of older adults.
- •iCap provides robust quantitative data about physical capability.
- •iCap captures gait and postural control data known as sensitive to ageing/pathology.
- •Methodology may have practical utility in a wide range of surveys and studies.
Main outcome measures
- Heaven B.
- O’Brien N.
- Evans E.H.
- et al.
2.1 Participant recruitment and measurement
2.3 Experimental protocol (iCap)
- (i)Locomotion – 4-m walk gait speed (×2): after a practice walk, participants walked at their usual speed between 2 markers. Manual and iCap timing began on the first footfall, i.e. participant's first step over the starting point. Recording ended after the participant completed the walk (manual) or last ‘purposeful’ footfall as determined by iCap [16,21]. Time to complete the 4 m walk was converted into a metres-per-second metric and averaged between trials:
- (ii)Lower limb strength – repeated sit-to-stand-to-sit (×2): after a practice, participants performed 5 sit-to-stand-to-sit posture transitions (PT), with arms folded across their chest, as quickly as possible. Participants were instructed to stand fully and not to touch the back of the chair during each repetition. Average time to complete both trials is presented.
- (iii)Lower limb strength with locomotion – TUG (×3): after a practice, participants stood up from a chair (height: 40–50 cm), walked 2 m at a normal pace, around a cone, back to the chair, turned and sat down. The TUG time was recorded manually as the time from initiation of chair rise to the time when the participant's back touched the backrest of the chair at the end of the manoeuvre. The average time across the three trials is presented.
- (iv)Postural control – standing balance: 5 tests were performed each lasting 50 s without shoes, arms folded across participant's chest, focusing on a wall-mounted fixed point (target) at a horizontal distance of 1 m. Variations included: (i) flat surface, feet together, eyes open (FLFTEO), (ii) flat surface, feet together, eyes closed (FLFTEC), (iii) foam surface3(50.0 cm × 41.0 cm × 6.0 cm), feet together, eyes open (FOFTEO), (iv) foam surface, feet together, eyes closed (FOFTEC) and (v) flat surface, tandem stance, eyes open (FLTMEO). BWM-based characteristics such as magnitude and frequencies were quantified for each test, Section 2.4.3Balance-pad Elite, AIREX, Switzerland.
- (v)Endurance – 2-min walk: participants walked continuously and as fast as they could without running. The route consisted of walking back and forth around cones placed 25 ft (7.62 m) apart. Once completed, the total distance walked was calculated manually. In addition, 14 gait characteristics sensitive to age/pathology were quantified by the BWM [18,19] during the duration of this test.
2.4 BWM algorithms
- (i)Algorithm #1 (locomotion/endurance): a continuous wavelet transform estimated the initial (IC) and final contact (FC) gait events []. Subsequently, the IC/FC times were used to record total time to complete the 4 m test as well as step, stride, stance and swing times.
- (ii)Algorithm #2 (lower extremity strength, TUG): PT and TUG were estimated from a refined version [] of a discrete wavelet transform based on the combination of tri-axial accelerometer data and peak/trough recognition [].
Wavelet based approach for posture transition estimation using a waist worn accelerometer.in: Conference proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society Annual Conference, 2007. 2007: 1884-1887
- Bidargaddi N.
- Klingbeil L.
- Sarela A.
- et al.
- (iii)Algorithm #3 (postural control): Jerk (rate of change of acceleration), root mean square (RMS, magnitude) and frequency components (95% percentile (F95%), ellipsis) were evaluated [10,17]. Due to its sensitivity, we present data within the mediolateral (ML) direction only []. (However, this methodology can also be applied to the AP and combined directions [10,17].)
- (iv)Algorithm #4 (endurance): complementary to the IC/FC algorithm, we applied the inverted pendulum model [] to estimate step length and hence total distance walked during the endurance test.
2.5 Statistical analysis
|Characteristic||Mean ± SD|
|Age (years)||61.30 ± 3.45|
|Height (m)||1.66 ± 0.09|
|Weight (kg)||73.53 ± 15.46|
|BMI (kg/m2)||26.79 ± 4.97|
3.1 iCap and manual recording agreement
|Task (n = 74)||Manual||BWM||Manual − BWM|
|Mean ± SD||Mean ± SD||ICC(2,1)|
4 m gait speed
|1.50 ± 0.24||1.60 ± 0.26||−0.10 ± 0.45||0.759|
|Lower limb strength (s)|
Repeated sit-to-stand-to sit
|7.06 ± 1.78||7.40 ± 2.04||−0.21 ± 0.82||0.983|
Lower limb strength & locomotion
|4.50 ± 0.77||4.11 ± 0.64||0.39 ± 0.74||0.926|
2 min walk
|171.41 ± 22.19||181.08 ± 24.70||9.67 ± 39.33||0.649|
3.2 iCap plus: postural control characteristics (standing balance)
|Trial (n = 74)||Postural control characteristics – median (range)|
|JerkML(m2/s5)||RMSML (mm/s2)||Ellipsis (mm2)||F95%ML (Hz)|
|(1) FLFTEO||0.017 (0.742)||0.008 (0.048)||0.073 (1.821)||2.030 (2.980)|
|(2) FLFTEC||0.028 (0.428)||0.009 (0.029)||0.096 (1.118)||1.900 (2.460)|
|(3) FOFTEO||0.041 (4.974)||0.010 (0.063)||0.128 (7.054)||1.810 (3.340)|
|(4) FOFTEC||0.227 (6.963)||0.019 (0.163)||0.671 (10.282)||1.660 (3.120)|
|(5) FLTMEO||0.054 (8.032)||0.011 (0.109)||0.130 (13.481)||2.260 (2.740)|
3.3 iCap plus: gait characteristics (endurance)
|Task (n = 66)||Gait characteristic||Mean ± SD|
|Endurance||Step velocity (m/s)||1.539 ± 0.196|
|2 min walk||Step length (m)||0.697 ± 0.081|
|Step time (s)||0.459 ± 0.034|
|Stance time (s)||0.589 ± 0.043|
|Step length variability (m)||0.101 ± 0.022|
|Task (n = 66)||Gait characteristic||Median (Range)|
|Endurance||Swing time variability (s)||0.061 (0.129)|
|2 min walk||Swing time (s)||0.330 (0.137)|
|Step time variability (s)||0.062 (0.129)|
|Step velocity variability (m/s)||0.222 (0.262)|
|Stance time variability (s)||0.062 (0.128)|
|Swing time asymmetry (s)||0.007 (0.033)|
|Step time asymmetry (s)||0.007 (0.041)|
|Stance time asymmetry (s)||0.006 (0.033)|
|Step length asymmetry (m)||0.009 (0.060)|
4.1 Validation of iCap
4.2 iCap plus
4.3 Use of existing technology and possible developments
- Mobilizing resources for well-being: implications for developing interventions in the retirement transition.Gerontologist. 2015; https://doi.org/10.1093/geront/gnu159
- Physical capability and the advantages and disadvantages of ageing: perceptions of older age by men and women in two British cohorts.Ageing Soc. 2014; 34: 452-471
- Objective measures of physical capability and subsequent health: a systematic review.Age Ageing. 2011; 40: 14-23
- Objectively measured physical capability levels and mortality: systematic review and meta-analysis.BMJ. 2010; 341: c4467
- Towards measurement of the healthy ageing phenotype in lifestyle-based intervention studies.Maturitas. 2013; 76: 189-199
- A life-course approach to healthy ageing: maintaining physical capability.Proc Nutr Soc. 2014; 73: 237-248
- SF-36 health survey: manual and interpretation guide: the health institute.The Health Institute, New England Medical Center, 1993
- Poverty in the United Kingdom.Pelican, Harmondsworth, UK1979
- Gait speed and survival in older adults.JAMA. 2011; 305: 50-58
- ISway: a sensitive, valid and reliable measure of postural control.J Neuroeng Rehabil. 2012; 9: 59
- A comparison of accelerometry and center of pressure measures during computerized dynamic posturography: a measure of balance.Gait Posture. 2011; 33: 594-599
- Instrumenting gait with an accelerometer: a system and algorithm examination.Med Eng Phys. 2015; 37: 400-407
- Vestibular function assessment using the NIH toolbox.Neurology. 2013; 80: S25-S31
- Motor assessment using the NIH toolbox.Neurology. 2013; 80: S65-S75
- NIH toolbox for assessment of neurological and behavioral function.Neurology. 2013; 80: S2-S6
- Instrumented assessment of test battery for physical capability using an accelerometer: a feasibility study.Physiol Meas. 2015; ([in press, Available online 20th April 2015])
- Trunk accelerometry as a measure of balance control during quiet standing.Gait Posture. 2002; 16: 60-68
- Independent domains of gait in older adults and associated motor and nonmotor attributes: validation of a factor analysis approach.J Gerontol A Biol Sci Med Sci. 2013; 68: 820-827
- Quantitative gait dysfunction and risk of cognitive decline and dementia.J Neurol Neurosurg Psychiatry. 2007; 78: 929-935
- Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. World Health Organization technical report series. vol. 854. 1995: 1-452
- An enhanced estimate of initial contact and final contact instants of time using lower trunk inertial sensor data.Gait Posture. 2012; 36: 316-318
- Wavelet based approach for posture transition estimation using a waist worn accelerometer.in: Conference proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society Annual Conference, 2007. 2007: 1884-1887
- Assessment of spatio-temporal gait parameters from trunk accelerations during human walking.Gait Posture. 2003; 18: 1-10
- Statistical methods for assessing agreement between two methods of clinical measurement.Lancet. 1986; 1: 307-310
- Concurrent validity of a trunk tri-axial accelerometer system for gait analysis in older adults.Gait Posture. 2009; 29: 444-448
- Foundations of clinical research: applications to practice.Prentice Hall Health, 2000
- Population reach and recruitment bias in a maintenance RCT in physically active older adults.J Phys Act Health. 2010; 7: 127-135
- Adult anthropometric measures overweight and obesity.in: Craig R. Mindell J. Health survey for England – 2013. Health & Social Care Information Centre, London2014
- Normative spatiotemporal gait parameters in older adults.Gait Posture. 2011; 34: 111-118
- Acceleration-based gait test for healthy subjects: reliability and reference data.Gait Posture. 2009; 30: 192-196
- A comparison of methods to detect postural transitions using a single tri-axial accelerometer. Engineering in Medicine and Biology Society (EMBC).in: 36th Annual International Conference of the IEEE2014. 2014: 6234-6237
- iTUG, a sensitive and reliable measure of mobility.IEEE Trans Neural Syst Rehabil Eng. 2010; 18: 303-310
- Is gait variability reliable in older adults and Parkinson's disease? Towards an optimal testing protocol.Gait Posture. 2013; 37: 580-585
- An instrumented timed up and go: the added value of an accelerometer for identifying fall risk in idiopathic fallers.Physiol Meas. 2011; 32: 2003-2018
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