Smartphone Monitoring of Gait and Balance During Irregular Surface Walking and Obstacle Crossing

As gait adaptation is vital for successful locomotion, the development of field-based tools to quantify gait in challenging real-world environments are crucial. The aims of this study were to assess the reliability and validity of a smartphone-based gait and balance assessment while walking on unobstructed and obstructed terrains using two phone placements. Furthermore, age-related differences in smartphone-derived gait strategies when navigating different walking conditions and environments were evaluated. By providing a method for evaluating gait in the simulated free-living environment, results of this study can elucidate the strategies young and older adults utilize to navigate obstructed and unobstructed walking paths. A total of 24 young and older adults ambulated indoors and outdoors under three conditions: level walking, irregular surface walking, and obstacle crossing. Android smartphones placed on the body and in a bag computed spatiotemporal gait (i.e., velocity, step time, step length, and cadence) and balance (i.e., center of mass (COM) displacement), with motion capture and video used to validate parameters in the laboratory and free-living environments, respectively. Reliability was evaluated using the intraclass correlation coefficient and validity was evaluated using Pearson's correlation and Bland-Altman analysis. A three-way ANOVA was used to assess outcome measures across group, condition, and environment. Results showed that smartphones were reliable and valid for measuring gait across all conditions, phone placements, and environments (ICC2,1: 0.606–0.965; Pearson's r: 0.72–1.00). Although body and bag placement demonstrated similar results for spatiotemporal parameters, accurate vertical COM displacement could only be obtained from the body placement. Older adults demonstrated a longer step time and lower cadence only during obstacle crossing, when compared to young adults. Furthermore, environmental differences in walking strategy were observed only during irregular surface walking. In particular, participants utilized a faster gait speed and a longer step length in the free-living environment, compared to the laboratory environment. In conclusion, smartphones demonstrate the potential for remote patient monitoring and home health care. Along with being easy-to-use, inexpensive, and portable, smartphones can accurately evaluate gait during both unobstructed and obstructed walking, indoors and outdoors.

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Day-to-Day Variability and Year-to-Year Reproducibility of Accelerometer-Measured Free-Living Sit-to-Stand Transitions Volume and Intensity among Community-Dwelling Older Adults

Sensors ◽

10.3390/s21186068 ◽

2021 ◽

Vol 21 (18) ◽

pp. 6068

Author(s):

Antti Löppönen ◽

Laura Karavirta ◽

Erja Portegijs ◽

Kaisa Koivunen ◽

Taina Rantanen ◽

...

Keyword(s):

Older Adults ◽

Angular Velocity ◽

Functional Disability ◽

Intraclass Correlation ◽

Living Environment ◽

Community Dwelling ◽

Free Living ◽

Sit To Stand ◽

Increased Risk ◽

Community Dwelling Older Adults

(1) Background: The purpose of this study was to evaluate the day-to-day variability and year-to-year reproducibility of an accelerometer-based algorithm for sit-to-stand (STS) transitions in a free-living environment among community-dwelling older adults. (2) Methods: Free-living thigh-worn accelerometry was recorded for three to seven days in 86 (women n = 55) community-dwelling older adults, on two occasions separated by one year, to evaluate the long-term consistency of free-living behavior. (3) Results: Year-to-year intraclass correlation coefficients (ICC) for the number of STS transitions were 0.79 (95% confidence interval, 0.70–0.86, p < 0.001), for mean angular velocity—0.81 (95% ci, 0.72–0.87, p < 0.001), and maximal angular velocity—0.73 (95% ci, 0.61–0.82, p < 0.001), respectively. Day-to-day ICCs were 0.63–0.72 for number of STS transitions (95% ci, 0.49–0.81, p < 0.001) and for mean angular velocity—0.75–0.80 (95% ci, 0.64–0.87, p < 0.001). Minimum detectable change (MDC) was 20.1 transitions/day for volume, 9.7°/s for mean intensity, and 31.7°/s for maximal intensity. (4) Conclusions: The volume and intensity of STS transitions monitored by a thigh-worn accelerometer and a sit-to-stand transitions algorithm are reproducible from day to day and year to year. The accelerometer can be used to reliably study STS transitions in free-living environments, which could add value to identifying individuals at increased risk for functional disability.

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Validity, Reliability and Sensitivity to Change of Three Consumer-grade Activity Trackers in Controlled and Free-living Conditions among Older Adults (Preprint)

10.2196/preprints.27155 ◽

2021 ◽

Author(s):

Kaja Kastelic ◽

Marina Dobnik ◽

Stefan Loefler ◽

Christian Hofer ◽

Nejc Šarabon

Keyword(s):

Physical Activity ◽

Older Adults ◽

Intraclass Correlation ◽

Sleep Time ◽

Living Conditions ◽

Percentage Error ◽

Sensitivity To Change ◽

Free Living ◽

Activity Trackers ◽

Free Living Conditions

BACKGROUND Wrist worn consumer-grade activity trackers are popular devices, developed mainly for personal use, but with the potential to be used also for clinical and research purposes. OBJECTIVE The objective of this study was to explore the validity, reliability and sensitivity to change of movement behaviours metrics from three popular activity trackers (POLAR Vantage M, Garmin Vivosport and Garmin Vivoactive 4s) in controlled and free-living conditions when worn by older adults. METHODS Participants (n = 28; 74 ± 5 years) underwent a videotaped laboratory protocol while wearing all three activity trackers. On a separate occasion, participants wore one (randomly assigned) activity tracker and a research grade physical activity monitor ActiGraph wGT3X-BT simultaneously for six consecutive days for comparisons. RESULTS Both Garmin activity trackers showed excellent performance for step counts, with mean absolute percentage error (MAPE) below 20 % and intraclass correlation coefficient (ICC2,1) above 0.90 (P < .05), while Polar Vantage M substantially over counted steps (MAPE = 84 % and ICC2,1 = 0.37 for free-living conditions). MAPE for sleep time was within 10 % for all the trackers tested, while far beyond 20 % for all the physical activity and calories burned outputs. Both Garmin trackers showed fair agreement (ICC2,1 = 0.58–0.55) for measuring calories burned when compared with ActiGraph. CONCLUSIONS Garmin Vivoactive 4s showed overall best performance, especially for measuring steps and sleep time in healthy older adults. Minimal detectible change was consistently lower for an average day measures than for a single day measure, but still relatively high. The results provided in this study could be used to guide choice on activity trackers aiming for different purposes – individual use/care, longitudinal monitoring or in clinical trial setting.

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Safety, Feasibility, and Reliability of the Maximal Step Length, Gait Speed, and Chair Test Measured by Seniors Themselves: The Senior Step Study

Journal of Aging and Physical Activity ◽

10.1123/japa.2013-0231 ◽

2015 ◽

Vol 23 (3) ◽

pp. 438-443 ◽

Cited By ~ 6

Author(s):

Kim T.J. Bongers ◽

Yvonne Schoon ◽

Maartje J. Graauwmans ◽

Marlies E. Hoogsteen-Ossewaarde ◽

Marcel G.M. Olde Rikkert

Keyword(s):

Older Adults ◽

Gait Speed ◽

Fall Risk ◽

Intraclass Correlation ◽

Step Length ◽

Community Dwelling ◽

Self Management ◽

Training Effect ◽

Community Dwelling Older Adults ◽

At Home

Self-management of mobility and fall risk might be possible if older adults could use a simple and safe self-test to measure their own mobility, balance, and fall risk at home. The aim of this study was to determine the safety, feasibility, and intraindividual reliability of the maximal step length (MSL), gait speed (GS), and chair test (CT) as potential self-tests for assessing mobility and fall risk. Fifty-six community-dwelling older adults performed MSL, GS, and CT at home once a week during a four-week period, wherein the feasibility, test-retest reliability, coefficients of variation, and linear mixed models with random effects of these three self-tests were determined. Forty-nine subjects (mean age 76.1 years [SD: 4.0], 19 females [42%]) completed the study without adverse effects. Compared with the other self-tests, MSL gave the most often (77.6%) valid measurement results and had the best intraclass correlation coefficients (0.95 [95% confidence interval: 0.91−0.97]). MSL and GS gave no significant training effect, whereas CT did show a significant training effect (p < .01). Community-dwelling older adults can perform MSL safely, correctly, and reliably, and GS safely and reliably. Further research is needed to study the responsiveness and beneficial effects of these self-tests on self-management of mobility and fall risk.

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Comparison of Fitbit One and ActivPAL3TM in Adults With Multiple Sclerosis in a Free-Living Environment

Journal for the Measurement of Physical Behaviour ◽

10.1123/jmpb.2020-0066 ◽

2021 ◽

Vol 4 (3) ◽

pp. 257-265

Author(s):

Golnoush Mehrabani ◽

Douglas P. Gross ◽

Saeideh Aminian ◽

Patricia J. Manns

Keyword(s):

Multiple Sclerosis ◽

Gait Speed ◽

Intraclass Correlation ◽

Correlation Coefficients ◽

Living Environment ◽

Free Living ◽

Step Counts ◽

Intraclass Correlation Coefficients ◽

Activity Tracker ◽

User Friendly

Walking is the most common and preferred way for people with multiple sclerosis (MS) to be active. Consumer-grade wearable activity monitors may be used as a tool to assist people with MS to track their walking by counting the number of steps. The authors evaluated the validity of Fitbit One activity tracker in individuals with MS by comparing step counts measured over a 7-day period against ActivPAL3TM (AP). Twenty-five ambulatory adults with MS with an average age 51.7 (10.2) years and gait speed 0.98 (0.47) m/s, median Expanded Disability Status Scale 5.5 (2.5–6.5), and 15 years post-MS diagnosis wore Fitbit One (using both waist and ankle placement) and AP for 7 consecutive days. Validity of Fitbit One for measuring step counts against AP was assessed using intraclass correlation coefficients (ICCs), Bland–Altman plots, and t tests. Regardless of wearing location (waist or ankle), there was good agreement between steps recorded by Fitbit One and AP (ICC: .86 [.82, .90]). The ankle-worn Fitbit measured steps more accurately (ICC: .91 [.81, .95]) than the waist-worn Fitbit (ICC: .81 [.62, .85]) especially in individuals (n = 12) who walked slowly (gait speed = 0.74 m/s). Fitbit One as a user-friendly, inexpensive, consumer-grade activity tracker can accurately record steps in persons with MS in a free-living environment.

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Is There a Sex Difference in Accelerometer Counts During Walking in Older Adults?

Journal of Physical Activity and Health ◽

10.1123/jpah.2012-0050 ◽

2014 ◽

Vol 11 (3) ◽

pp. 626-637 ◽

Cited By ~ 7

Author(s):

Dane R. Van Domelen ◽

Paolo Caserotti ◽

Robert J. Brychta ◽

Tamara B. Harris ◽

Kushang V. Patel ◽

...

Keyword(s):

Older Adults ◽

Sex Difference ◽

Walking Speed ◽

Vertical Axis ◽

Step Length ◽

Walk Test ◽

Free Living ◽

Males And Females ◽

6 Minute Walk Test ◽

Minute Walk

Background:Accelerometers have emerged as a useful tool for measuring free-living physical activity in epidemiological studies. Validity of activity estimates depends on the assumption that measurements are equivalent for males and females while performing activities of the same intensity. The primary purpose of this study was to compare accelerometer count values in males and females undergoing a standardized 6-minute walk test.Methods:The study population was older adults (78.6 ± 4.1 years) from the AGES-Reykjavik Study (N = 319). Participants performed a 6-minute walk test at a self-selected fast pace while wearing an ActiGraph GT3X at the hip. Vertical axis counts·s−1 was the primary outcome. Covariates included walking speed, height, weight, BMI, waist circumference, femur length, and step length.Results:On average, males walked 7.2% faster than females (1.31 vs. 1.22 m·s−1, P < .001) and had 32.3% greater vertical axis counts·s−1 (54.6 vs. 39.4 counts·s−1, P < .001). Accounting for walking speed reduced the sex difference to 19.2% and accounting for step length further reduced the difference to 13.4% (P < .001).Conclusion:Vertical axis counts·s−1 were disproportionally greater in males even after adjustment for walking speed. This difference could confound free-living activity estimates.

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Validity Evaluation of the Fitbit Charge2 and the Garmin vivosmart HR+ in Free-Living Environments in an Older Adult Cohort (Preprint)

10.2196/preprints.13084 ◽

2018 ◽

Author(s):

Salvatore Tedesco ◽

Marco Sica ◽

Andrea Ancillao ◽

Suzanne Timmons ◽

John Barton ◽

...

Keyword(s):

Older Adults ◽

Energy Expenditure ◽

Vigorous Physical Activity ◽

Living Environment ◽

Percentage Error ◽

Free Living ◽

Healthy Older Adults ◽

Activity Trackers ◽

Sleep Parameters ◽

Highly Correlated

BACKGROUND Few studies have investigated the validity of mainstream wrist-based activity trackers in healthy older adults in real life, as opposed to laboratory settings. OBJECTIVE This study explored the performance of two wrist-worn trackers (Fitbit Charge 2 and Garmin vivosmart HR+) in estimating steps, energy expenditure, moderate-to-vigorous physical activity (MVPA) levels, and sleep parameters (total sleep time [TST] and wake after sleep onset [WASO]) against gold-standard technologies in a cohort of healthy older adults in a free-living environment. METHODS Overall, 20 participants (>65 years) took part in the study. The devices were worn by the participants for 24 hours, and the results were compared against validated technology (ActiGraph and New-Lifestyles NL-2000i). Mean error, mean percentage error (MPE), mean absolute percentage error (MAPE), intraclass correlation (ICC), and Bland-Altman plots were computed for all the parameters considered. RESULTS For step counting, all trackers were highly correlated with one another (ICCs>0.89). Although the Fitbit tended to overcount steps (MPE=12.36%), the Garmin and ActiGraph undercounted (MPE 9.36% and 11.53%, respectively). The Garmin had poor ICC values when energy expenditure was compared against the criterion. The Fitbit had moderate-to-good ICCs in comparison to the other activity trackers, and showed the best results (MAPE=12.25%), although it underestimated calories burned. For MVPA levels estimation, the wristband trackers were highly correlated (ICC=0.96); however, they were moderately correlated against the criterion and they overestimated MVPA activity minutes. For the sleep parameters, the ICCs were poor for all cases, except when comparing the Fitbit with the criterion, which showed moderate agreement. The TST was slightly overestimated with the Fitbit, although it provided good results with an average MAPE equal to 10.13%. Conversely, WASO estimation was poorer and was overestimated by the Fitbit but underestimated by the Garmin. Again, the Fitbit was the most accurate, with an average MAPE of 49.7%. CONCLUSIONS The tested well-known devices could be adopted to estimate steps, energy expenditure, and sleep duration with an acceptable level of accuracy in the population of interest, although clinicians should be cautious in considering other parameters for clinical and research purposes.

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Validity, Reliability and Sensitivity to Change of Three Consumer-Grade Activity Trackers in Controlled and Free-Living Conditions among Older Adults

Sensors ◽

10.3390/s21186245 ◽

2021 ◽

Vol 21 (18) ◽

pp. 6245

Author(s):

Kaja Kastelic ◽

Marina Dobnik ◽

Stefan Löfler ◽

Christian Hofer ◽

Nejc Šarabon

Keyword(s):

Older Adults ◽

Intraclass Correlation ◽

Sleep Time ◽

Living Conditions ◽

Percentage Error ◽

Sensitivity To Change ◽

Free Living ◽

Step Counts ◽

Activity Trackers ◽

Free Living Conditions

Wrist-worn consumer-grade activity trackers are popular devices, developed mainly for personal use. This study aimed to explore the validity, reliability and sensitivity to change of movement behaviors metrics from three activity trackers (Polar Vantage M, Garmin Vivoactive 4s and Garmin Vivosport) in controlled and free-living conditions when worn by older adults. Participants (n = 28; 74 ± 5 years) underwent a videotaped laboratory protocol while wearing all three trackers. On a separate occasion, participants (n = 17 for each of the trackers) wore one (randomly assigned) tracker and a research-grade activity monitor ActiGraph wGT3X-BT simultaneously for six consecutive days. Both Garmin trackers showed excellent performance for step counts, with a mean absolute percentage error (MAPE) below 20% and intraclass correlation coefficient (ICC2,1) above 0.90 (p < 0.05). The MAPE for sleep time was within 10% for all the trackers tested, while it was far beyond 20% for all other movement behaviors metrics. The results suggested that all three trackers could be used for measuring sleep time with a high level of accuracy, and both Garmin trackers could also be used for step counts. All other output metrics should be used with caution. The results provided in this study could be used to guide choice on activity trackers aiming for different purposes—individual use, longitudinal monitoring or in clinical trial setting.

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Measurement of Sitting Time in Older Adults With and Without Alzheimer’s Disease

Journal for the Measurement of Physical Behaviour ◽

10.1123/jmpb.2018-0002 ◽

2018 ◽

Vol 1 (2) ◽

pp. 70-78

Author(s):

Amber Watts ◽

Mauricio Garnier-Villarreal ◽

Paul Gardiner

Keyword(s):

Alzheimer’S Disease ◽

Older Adults ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Sedentary Time ◽

Early Stage ◽

Living Environment ◽

Sitting Time ◽

Free Living ◽

Physical Limitations

Time spent being sedentary is associated with poorer cognitive function and risk of developing Alzheimer’s disease (AD). The present study aimed to compare patterns of sitting in a free-living environment among older adults with and without early stage AD who were similar in physical limitations, body mass, and cardiorespiratory capacity. We also compared estimates of sitting patterns between two different monitors (postural and non-postural) with different body placements (thigh-worn vs. hip-worn). Comparing older adults without cognitive impairment to those with early AD, we found that although there was no difference in the total amount of daily sitting time (p = .52), the AD group tended to have longer durations of sitting than those without AD. Inclinometry data from the hip-worn ActiGraph GT3X+ consistently underestimated time spent sitting compared to the thigh worn monitor activPAL™ (hours per day, proportion of waking hours, number of sitting bouts greater than 30 minutes, and duration of sitting bouts). Our results have implications for prevention strategies to reduce sedentary time, which is predominantly sitting, in persons with cognitive impairment and highlight the importance of monitor selection and placement for the accurate assessment of sitting patterns in this population.

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Classical Machine Learning versus Deep Learning for the Older Adults Free-Living Activity Classification

Sensors ◽

10.3390/s21144669 ◽

2021 ◽

Vol 21 (14) ◽

pp. 4669

Author(s):

Muhammad Awais ◽

Lorenzo Chiari ◽

Espen A. F. Ihlen ◽

Jorunn L. Helbostad ◽

Luca Palmerini

Keyword(s):

Machine Learning ◽

Older Adults ◽

Deep Learning ◽

Elderly Population ◽

Inertial Sensor ◽

Living Environment ◽

Frame Rate ◽

Sensor Data ◽

Support Vector ◽

Free Living

Physical activity has a strong influence on mental and physical health and is essential in healthy ageing and wellbeing for the ever-growing elderly population. Wearable sensors can provide a reliable and economical measure of activities of daily living (ADLs) by capturing movements through, e.g., accelerometers and gyroscopes. This study explores the potential of using classical machine learning and deep learning approaches to classify the most common ADLs: walking, sitting, standing, and lying. We validate the results on the ADAPT dataset, the most detailed dataset to date of inertial sensor data, synchronised with high frame-rate video labelled data recorded in a free-living environment from older adults living independently. The findings suggest that both approaches can accurately classify ADLs, showing high potential in profiling ADL patterns of the elderly population in free-living conditions. In particular, both long short-term memory (LSTM) networks and Support Vector Machines combined with ReliefF feature selection performed equally well, achieving around 97% F-score in profiling ADLs.

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Continuous home monitoring of Parkinson’s disease using inertial sensors: A systematic review

PLoS ONE ◽

10.1371/journal.pone.0246528 ◽

2021 ◽

Vol 16 (2) ◽

pp. e0246528

Author(s):

Marco Sica ◽

Salvatore Tedesco ◽

Colum Crowe ◽

Lorna Kenny ◽

Kevin Moore ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Inertial Sensors ◽

Wearable Sensors ◽

Home Monitoring ◽

Relevant Information ◽

Step Length ◽

Living Environment ◽

Free Living ◽

Gait Impairments

Parkinson’s disease (PD) is a progressive neurological disorder of the central nervous system that deteriorates motor functions, while it is also accompanied by a large diversity of non-motor symptoms such as cognitive impairment and mood changes, hallucinations, and sleep disturbance. Parkinsonism is evaluated during clinical examinations and appropriate medical treatments are directed towards alleviating symptoms. Tri-axial accelerometers, gyroscopes, and magnetometers could be adopted to support clinicians in the decision-making process by objectively quantifying the patient’s condition. In this context, at-home data collections aim to capture motor function during daily living and unobstructedly assess the patients’ status and the disease’s symptoms for prolonged time periods. This review aims to collate existing literature on PD monitoring using inertial sensors while it focuses on papers with at least one free-living data capture unsupervised either directly or via videotapes. Twenty-four papers were selected at the end of the process: fourteen investigated gait impairments, eight of which focused on walking, three on turning, two on falls, and one on physical activity; ten articles on the other hand examined symptoms, including bradykinesia, tremor, dyskinesia, and motor state fluctuations in the on/off phenomenon. In summary, inertial sensors are capable of gathering data over a long period of time and have the potential to facilitate the monitoring of people with Parkinson’s, providing relevant information about their motor status. Concerning gait impairments, kinematic parameters (such as duration of gait cycle, step length, and velocity) were typically used to discern PD from healthy subjects, whereas for symptoms’ assessment, researchers were capable of achieving accuracies of over 90% in a free-living environment. Further investigations should be focused on the development of ad-hoc hardware and software capable of providing real-time feedback to clinicians and patients. In addition, features such as the wearability of the system and user comfort, set-up process, and instructions for use, need to be strongly considered in the development of wearable sensors for PD monitoring.

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