Dataset Information

Inferring Physical Function From Wearable Activity Monitors: Analysis of Free-Living Activity Data From Patients With Knee Osteoarthritis.

ABSTRACT:

Background

Clinical assessments for physical function do not objectively quantify routine daily activities. Wearable activity monitors (WAMs) enable objective measurement of daily activities, but it remains unclear how these map to clinically measured physical function measures.

Objective

This study aims to derive a representation of physical function from daily measurements of free-living activity obtained through a WAM. In addition, we evaluate our derived measure against objectively measured function using an ordinal classification setup.

Methods

We defined function profiles representing average time spent in a set of pattern classes over consecutive days. We constructed a function profile using minute-level activity data from a WAM available from the Osteoarthritis Initiative. Using the function profile as input, we trained statistical models that classified subjects into quartiles of objective measurements of physical function as measured through the 400-m walk test, 20-m walk test, and 5 times sit-stand test. Furthermore, we evaluated model performance on held-out data.

Results

The function profile derived from minute-level activity data can accurately predict physical performance as measured through clinical assessments. Using held-out data, the Goodman-Kruskal Gamma statistic obtained in classifying performance values in the first quartile, interquartile range, and the fourth quartile was 0.62, 0.53, and 0.51 for the 400-m walk, 20-m walk, and 5 times sit-stand tests, respectively.

Conclusions

Function profiles accurately represent physical function, as demonstrated by the relationship between the profiles and clinically measured physical performance. The estimation of physical performance through function profiles derived from free-living activity data may enable remote functional monitoring of patients.

SUBMITTER: Agarwal V

PROVIDER: S-EPMC6315255 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Inferring Physical Function From Wearable Activity Monitors: Analysis of Free-Living Activity Data From Patients With Knee Osteoarthritis.

Agarwal Vibhu V Smuck Matthew M Tomkins-Lane Christy C Shah Nigam H NH

JMIR mHealth and uHealth 20181218 12

<h4>Background</h4>Clinical assessments for physical function do not objectively quantify routine daily activities. Wearable activity monitors (WAMs) enable objective measurement of daily activities, but it remains unclear how these map to clinically measured physical function measures.<h4>Objective</h4>This study aims to derive a representation of physical function from daily measurements of free-living activity obtained through a WAM. In addition, we evaluate our derived measure against object ...[more]

PMID: 30394876

Similar Datasets

Project description:BackgroundA majority of individuals with osteoarthritis (OA) are insufficiently physically active. Self-monitoring with wearable activity trackers (WAT) could promote physical activity (PA), and increased knowledge of PA patterns and adherence to using a WAT is needed. The aim of this study was to describe PA patterns and adherence to WAT-use during an intervention among participants of working age with hip and/or knee OA. The study further explores the correlation between self-reported joint function and PA.MethodsIndividuals of working age with hip and/or knee OA who used a WAT, Fitbit Flex 2, for 12 weeks were included. Participants monitored their PA in the Fitbit-app. An activity goal of 7,000 steps/day was set. Steps and minutes in light (L), moderate and vigorous (MV) PA were collected from the Fitbit. Self-reported joint function (HOOS/KOOS) was completed. Data was analyzed with linear mixed models and Spearman's rank correlation.ResultsSeventy-five participants (45-66 years) walked on average 10 593 (SD 3431) steps/day, spent 248.5 (SD 42.2) minutes in LPA/day, 48.1 (SD 35.5) minutes in MVPA/day, 336.0 (SD 249.9) minutes in MVPA/week and used the Fitbit for an average of 88.4 % (SD 11.6) of the 12-week period. 86.7 % took > 7,000 steps/day and 77.3 % spent > 150 min in MVPA/week. Mean daily steps/week decreased significantly over the 12 weeks (β-coefficient - 117, 95 % CI -166 to -68, p = < 0.001) as well as mean daily minutes in LPA/week (β-coefficient - 2.3, 95 % CI -3.3 to -1.4, p = < 0.001), mean daily minutes in MVPA/week (β-coefficient - 0.58, 95 % CI -1.01 to -0.16, p = 0.008) and mean adherence to Fitbit-use per week (β-coefficient - 1.3, 95 % CI -1.8 to -0.8, p = < 0.001). There were no significant correlations between function (HOOS/KOOS) and PA.ConclusionsThe majority of participants reached 7,000 steps/day and the recommended 150 min in MVPA per week. However, PA decreased slightly but gradually over time. Adherence to using the Fitbit was high but also decreased during the intervention. Understanding PA patterns and the use of a Fitbit to promote PA could be beneficial in tailoring interventions for individuals with hip and/or knee OA.

Project description:BackgroundFew instruments that measure physical activity (PA) can accurately quantify PA performed at light and moderate intensities, which is particularly relevant in older adults. The evidence of their reliability in free-living conditions is limited.ObjectiveThe study objectives were: (1) to determine the test-retest reliability of the Actigraph (ACT), SenseWear Armband (SWA), and Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire in assessing free-living PA at light and moderate intensities in people after total knee arthroplasty; (2) to compare the reliability of the 3 instruments relative to each other; and (3) to determine the reliability of commonly used monitoring time frames (24 hours, waking hours, and 10 hours from awakening).DesignA one-group, repeated-measures design was used.MethodsParticipants wore the activity monitors for 2 weeks, and the CHAMPS questionnaire was completed at the end of each week. Test-retest reliability was determined by using the intraclass correlation coefficient (ICC [2,k]) to compare PA measures from one week with those from the other week.ResultsData from 28 participants who reported similar PA during the 2 weeks were included in the analysis. The mean age of these participants was 69 years (SD=8), and 75% of them were women. Reliability ranged from moderate to excellent for the ACT (ICC=.75-.86) and was excellent for the SWA (ICC=.93-.95) and the CHAMPS questionnaire (ICC=.86-.92). The 95% confidence intervals (95% CI) of the ICCs from the SWA were the only ones within the excellent reliability range (.85-.98). The CHAMPS questionnaire showed systematic bias, with less PA being reported in week 2. The reliability of PA measures in the waking-hour time frame was comparable to that in the 24-hour time frame and reflected most PA performed during this period.LimitationsReliability may be lower for time intervals longer than 1 week.ConclusionsAll PA measures showed good reliability. The reliability of the ACT was lower than those of the SWA and the CHAMPS questionnaire. The SWA provided more precise reliability estimates. Wearing PA monitors during waking hours provided sufficiently reliable measures and can reduce the burden on people wearing them.

Project description:BACKGROUND:Practice guidelines emphasize the use of exercise and weight reduction as the first line of management for knee osteoarthritis (OA). However, less than half of the people with mild OA participate in moderate intensity physical activity. Given that physical activities have been shown to reduce pain, improve quality of life, and have the potential to reduce the progression of joint damage, many people with OA are missing the benefits of this inexpensive intervention. OBJECTIVE:The objectives of this study are (1) to develop a behavioral theory-informed Internet intervention called Osteoarthritis Physical Activity & Exercise Net (OPEN) for people with previously undiagnosed knee OA, and (2) to assess the efficacy of the OPEN website for improving physical activity participation through a proof-of-concept study. METHODS:OPEN was developed based on the theory of planned behavior. Efficacy of this online intervention is being assessed by an ongoing proof-of-concept, single-blind randomized controlled trial in British Columbia, Canada. We are currently recruiting participants and plan to recruit a total of 252 sedentary people with previously undiagnosed knee OA using a set of validated criteria. Half of the participants will be randomized to use OPEN and receive an OA education pamphlet. The other half only will receive the pamphlet. Participants will complete an online questionnaire at baseline, 3 months, and 6 months about their participation in physical activities, health-related quality of life, and motivational outcomes. In addition, we will perform an aerobic fitness test in a sub-sample of participants (n=20 per study arm). In the primary analysis, we will use logistic regression to compare the proportion of participants reporting being physically active at or above the recommended level in the 2 groups, adjusting for baseline measurement, age, and sex. RESULTS:This study evaluates a theory-informed behavioral intervention at a time when people affected with OA tend to be more motivated to adopt an active lifestyle (ie, at the early stage of OA). Our approach, which consisted of the identification of early knee OA followed immediately by an online intervention that directly targets physical inactivity, can be easily implemented across communities. CONCLUSIONS:Our online intervention directly targets physical inactivity at a time when the joint damage tends to be mild. If OPEN is found to be effective in changing long-term physical activity behaviors, it opens further opportunities to promote early diagnosis and to implement lifestyle interventions. TRIAL REGISTRATION:Clinicaltrial.gov: NCT01608282; http://clinicaltrials.gov/ct2/show/NCT01608282 (Archived by WebCite at http://www.webcitation.org/6G7sBBayI).

Dataset Information

Inferring Physical Function From Wearable Activity Monitors: Analysis of Free-Living Activity Data From Patients With Knee Osteoarthritis.

Background

Objective

Methods

Results

Conclusions

Publications

Inferring Physical Function From Wearable Activity Monitors: Analysis of Free-Living Activity Data From Patients With Knee Osteoarthritis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets