Wearable Activity Monitor Research Articles

Wearable Sensor Technology Efficacy in Peripheral Vascular Disease (wSTEP): A Randomized Controlled Trial.

To evaluate the effect of using wearable activity monitors (WAMs) in patients with intermittent claudication (IC) within a single-center randomized controlled trial. WAMs allow users to set daily activity targets and monitor their progress. They may offer an alternative treatment to supervised exercise programs (SEPs) for patients with IC. Thirty-seven patients with IC were recruited and randomized into intervention or control group. The intervention consisted of a feedback-enabled, wrist-worn activity monitor (WAM) in addition to access to SEP. The control group was given access to SEP only. The outcome measures were maximum walking distance (MWD), claudication distance (CD), and quality of life as measured by the VascuQol questionnaire. Participants were assessed upon recruitment, and at 3, 6, and 12 months. Patients in the WAM group showed significant improvement in MWD at 3 and 6 months (80-112 m, to 178 m; P < 0.001), which was sustained at 12 months. The WAM group also increased CD (40 vs 110 m; P < 0.001) and VascuQol score (4.7 vs 5.8; P = 0.004). The control group saw a temporary increase in VascuQol score at 6 months (4.5 vs 4.7; P = 0.028), but no other improvements in MWD or CD were observed. Significantly higher improvements in MWD were seen in the WAM group compared with that in the control group at 6 months (82 vs -5 m; P = 0.009, r = 0.47) and 12 months (69 vs 7.5 m; P = 0.011, r = 0.52). The study demonstrates the significant, sustained benefit of WAM-led technologies for patients with IC. This potentially resource-sparing intervention is likely to provide a valuable adjunct or alternative to SEP.

Feasibility of Wearable Physical Activity Monitors in Patients With Cancer.

The feasibility of using physical activity monitors (PAMs) to measure functional status in patients with cancer is unclear. We aimed to determine the feasibility of using PAMs to longitudinally assess physical activity and performance status (PS) in patients with cancer. Patients with cancer who had Eastern Cooperative Oncology Group (ECOG) PS of 0 to 2 and were receiving systemic therapy were enrolled in a prospective pilot trial of PAM use. Feasibility was defined as patients using the PAM for > 50% of the observation period. We correlated PAM-reported measures with scores from ECOG PS and quality-of-life tools (Functional Assessment of Cancer Therapy-General [FACT-G], Quick Inventory of Depressive Symptoms-Self-Rated 16 [QIDS-SR16], and Brief Fatigue Inventory [BFI]) using Pearson's correlation test. Patients were surveyed regarding their experience with PAMs at study completion. In all, 24 patients were enrolled; mean age was 54 years, 16 (67%) were women, and 19 (79%) were white. Twenty-three patients (96%) met the primary end point of feasibility. The median duration of follow-up was 69 days. Mean PAM-measured steps for ECOG PS of 0, 1, and 2 were 5,911, 1,890, and 845 steps per day, respectively ( P = .002). Minimum steps per day correlated with BFI ( r = -0.53; P < .01), FACT-G ( r = 0.45; P = .02), and QIDS-SR16 ( r = -0.57; P < .01). Eighteen patients (75%) reported a positive experience with the PAM. PAMs are a feasible tool for measuring long-term physical activity in patients with cancer who are receiving systemic therapy. PAM-derived measures correlated with clinician-assessed PS.

A Pilot Study to Assess the Feasibility of Collecting and Transmitting Clinical Trial Data with Mobile Technologies

Background: The use of mobile technologies for data capture and transmission has the potential to streamline clinical trials, but researchers lack methods for collecting, processing, and interpreting data from these tools. Objectives: To assess the performance of a technical platform for collecting and transmitting data from six mobile technologies in the clinic and at home, to apply methods for comparing them to clinical standard devices, and to measure their usability, including how willing subjects were to use them on a regular basis. Methods: In part 1 of the study, conducted over 3 weeks in the clinic, we tested two device pairs (mobile vs. clinical standard blood pressure monitor and mobile vs. clinical standard spirometer) on 25 healthy volunteers. In part 2 of the study, conducted over 3 days both in the clinic and at home, we tested the same two device pairs as in part 1, plus four additional pairs (mobile vs. clinical standard pulse oximeter, glucose meter, weight scale, and activity monitor), on 22 healthy volunteers. Results: Data collection reliability was 98.1% in part 1 of the study and 95.8% in part 2 (the percentages exclude the wearable activity monitor, which collects data continuously). In part 1, 20 of 1,049 overall expected measurements were missing (1.9%), and in part 2, 45 of 1,083 were missing (4.2%). The most common reason for missing data was a single malfunctioning spirometer (13 of 20 total missed readings) in part 1, and that the subject did not take the measurement (22 of 45 total missed readings) in part 2. Also in part 2, a higher proportion of at-home measurements than in-clinic readings were missing (12.6 vs. 2.7%). The data from this experimental study were unable to establish repeatability or agreement for every mobile technology; only the pulse oximeter demonstrated repeatability, and only the weight scale demonstrated agreement with the clinical standard device. Most mobile technologies received high “willingness to use” ratings from the patients on the questionnaires. Conclusions: This study demonstrated that the wireless data transmission and processing platform was dependable. It also identified three critical areas of study for advancing the use of mobile technologies in clinical research: (1) if a mobile technology captures more than one type of endpoint (such as blood pressure and pulse), repeatability and agreement may need to be established for each endpoint to be included in a clinical trial; (2) researchers need to develop criteria for excluding invalid device readings (to be identified by algorithms in real time) for the population studied using ranges based on accumulated subject data and established norms; and (3) careful examination of a mobile technology’s performance (reliability, repeatability, and agreement with accepted reference devices) during pilot testing is essential, even for medical devices approved by regulators.

Improving Physical Activity Through Adjunct Telerehabilitation Following Total Knee Arthroplasty: Randomized Controlled Trial Protocol.

Physical activity remains low and nearly unchanged from preoperative levels following total knee arthroplasty (TKA), and this is thought to underlie long-term functional limitations, secondary health problems, and higher health care costs after TKA. Our objective is to determine whether a telehealth-based intervention could improve physical activity and functional outcomes after TKA. The design is a 2-arm, parallel, assessor-blinded, randomized controlled trial with baseline, midintervention, postintervention, and 6-month follow-up assessments. The setting is one academic medical center and one Veterans Affairs health care system. One hundred US military veterans (aged 50-85 years) scheduled for unilateral TKA will participate in this study. The telehealth-based intervention to change physical activity behavior will be delivered through 10 sessions each of 30 minutes over a 12-week period. Participants will be provided with a wearable physical activity monitor to receive feedback on step count and guide goal-setting. Control participants will receive telehealth-based education on nonbehavioral aspects of health for the same frequency and duration as the intervention group. For both groups, telehealth sessions will occur concurrently with standardized outpatient rehabilitation. The primary outcome will be change in physical activity, assessed as daily step counts measured using an accelerometer-based sensor. Secondary outcomes will be measured using the Life-Space Assessment questionnaire and change in physical function (30-Second Chair-Stand Test, Timed "Up & Go" Test, Six-Minute Walk Test, Western Ontario and McMaster Universities Osteoarthritis Index, and Veterans RAND 12-Item Health Survey). Participant and interventionist blinding is not possible. This trial will assess the efficacy of a novel behavior-change intervention to improve physical activity and physical function in patients after TKA. Effective physical activity behavior change could provide clinicians with a technique to augment current practice and resolve poor physical activity outcomes, long-term health problems, and high costs following TKA.

Sleep and Exercise in Emergency Medicine Residents: An Observational Pilot Study Exploring the Utility of Wearable Activity Monitors for Monitoring Wellness.

IntroductionBurnout is well-documented in residents and emergency physicians. Wellness initiatives are becoming increasingly prevalent, but there is a lack of data supporting their efficacy. In some populations, a relationship between sleep, exercise, and wellness has been documented; however, this relationship has not been established in emergency medicine (EM) residents or physicians. We aim to determine whether a wearable activity monitor is a feasible method of evaluating exercise and sleep quality and quantity in emergency medicine residents and if these assessments are associated with greater perceived wellness.MethodsTwenty EM residents from two training sites wore a wearable activity monitor (Fitbit ChargeTM, Fitbit, Inc., San Francisco, CA, USA) during a four-week EM rotation. The Fitbit recorded data on sleep quantity (minutes sleeping) and quality (sleep disruptions), as well as exercise quantity and quality (daily step count, daily active minutes performing activity of 3 - 6, and > 6 metabolic equivalents). Participants completed an end-of-rotation Perceived Wellness Survey (PWS), which provided information on six domains of personal wellness (psychological, emotional, social, physical, spiritual, and intellectual). PWS levels were compared between groups of subjects with higher or lower levels of activity and sleep (i.e., above and below the median subject-averaged values) using the Mann-Whitney U test. Other subject characteristics were similarly assessed for their association with PWS. When a possible confounding effect was seen, the data was stratified and reviewed using a scatterplot.ResultsOf the 28 eligible residents, 23 agreed to participate. Of these, 20 and 16 wore the device for at least 50% of the respective days and nights during the observation period. Two devices were lost. One PWS was not completed. There was no statistically significant correlation between resident perceived wellness survey scores, sleep interruptions, average daily sleep minutes, daily step count, or average daily active minutes for the sample overall. However, first-year residents and residents from years two to five reported different median PWS scores of 13.9 and 17.1, respectively. Further exploration by the training group suggested that step counts may correlate with wellness in participants in their first year of residency, while the quantity of sleep may have an association with wellness in participants in years two through five of their residency.ConclusionUsing wearable activity monitor devices to capture sleep and exercise data among residents does not seem to be an effective approach. Our data does not support our hypothesis that overall resident wellness was associated with exercise and sleep quality and quantity as measured by such a device. These results are counterintuitive and may be complicated by several measurement-related limitations and the possibility that benefits depend on the stage of training.

Wearable activity monitors to assess performance status and predict clinical outcomes in advanced cancer patients

An objective evaluation of patient performance status (PS) is difficult because patients spend the majority of their time outside of the clinic, self-report to providers, and undergo dynamic changes throughout their treatment experience. Real-time, objective activity data may allow for a more accurate assessment of PS and physical function, while reducing the subjectivity and bias associated with current assessments. Consenting patients with advanced cancer wore a wearble activity monitor for three consecutive visits in a prospective, single-cohort clinical trial. Provider-assessed PS (ECOG/Karnofsky) and NIH PROMIS® patient-reported outcomes (PROs) were assessed at each visit. Associations between wearable activity monitor metrics (steps, distance, stairs) and PS, clinical outcomes (adverse events, hospitalizations, survival), and PROs were assessed using correlation statistics and in multivariable logistic regression models. Thirty-seven patients were evaluated (54% male, median 62 years). Patients averaged 3700 steps, 1.7 miles, and 3 flights of stairs per day. Highest correlations were observed between average daily steps and ECOG-PS and KPS (r = 0.63 and r = 0.69, respectively p < 0.01). Each 1000 steps/day increase was associated with reduced odds for adverse events (OR: 0.34, 95% CI 0.13, 0.94), hospitalizations (OR: 0.21 95% CI 0.56, 0.79), and hazard for death (HR: 0.48 95% CI 0.28–0.83). Significant correlations were also observed between activity metrics and PROs. Our trial demonstrates the feasibility of using wearable activity monitors to assess PS in advanced cancer patients and suggests their potential use to predict clinical and patient-reported outcomes. These findings should be validated in larger, randomized trials.

Development of a Web Portal for Physical Activity and Symptom Tracking in Oncology Patients: Protocol for a Prospective Cohort Study.

BackgroundSignificant benefits accrue from increasing physical activity levels in people with a history of cancer. Physical activity levels can be increased using behavioral change interventions in this population. Access to Web portals and provision of activity monitors to provide feedback may support behavior change by encouraging patient engagement in physical therapy. The Web portal evaluated in this study will provide a system to monitor physical activity and sleep, for use by both clinician and patient, along with symptom and health-related quality of life tracking capabilities.ObjectiveThe aim of this study was to outline a protocol for a feasibility study focused on a Web-based portal that provides activity monitoring and personalized messaging to increase physical activity in people with cancer.MethodsUsing a longitudinal cohort design, people with cancer will be serially allocated to 3 intervention cohorts of 20 participants each and followed for 10 weeks. Cohort 1 will be provided a wearable activity monitor and access to a Web-based portal. Cohort 2 will receive the same content as Cohort 1 and in addition will receive a weekly activity summary message. Cohort 3 will receive the same content as Cohorts 1 and 2 and in addition will receive a personalized weekly coaching message. Feasibility of the use of the portal is the primary outcome.ResultsResults are expected in early 2018. Outcome measures will include goal attainment and completion rate.ConclusionsThis study will provide information about the feasibility of investigating eHealth initiatives to promote physical activity in people with cancer.Registered Report IdentifierRR1-10.2196/9586

The Validity Of A Commercially-available, Low-cost Accelerometer In A Free-living Setting

Wearable activity monitors are a popular tool for the measurement of physical activity in the consumer market. However, much of the existing evidence assessing the validity of these commercially-available activity monitors is laboratory-based. Because these monitors will typically be used by consumers outside of a laboratory setting additional research assessing the validity of wearable activity monitors in free-living environments is warranted. PURPOSE: To assess the ability of a low cost, wearable activity monitor marketed to consumer (Movband 3) to measure physical activity behavior in a free-living setting against a previously-validated, research-grade accelerometer (Actigraph GT1M). METHODS: Sixteen participants (n = five females, 27.0 ± 6.0 years old) were given both the commercially-available Movband (mounted on the wrist) and the research-grade Actigraph (mounted on the waist) to wear over the period of one week during free-living activity. Participants were required to simultaneously wear the two monitors for a minimum of five hours per day on five of the seven days. Participants completed daily diaries indicating the time of day in which the two monitors were worn. Physical activity data from each monitor was then divided by the duration of time participants wore the two monitors. Therefore, physical activity data for each monitor was expressed as activity counts/minute worn for each day. Pearson’s correlation analyses were then performed to assess the relationship between counts/minute of the two monitors for each participant individually across all days the two devices were worn for a minimum of five hours. These individual correlation coefficients were then averaged across all participants and presented as a single value. RESULTS: There was a large, positive effect size for the association (r = 0.57) between Movband and Actigraph activity counts/minute during free- living activity. In other words, as physical activity counts/minute increased in the Movband, activity also increased in the Actigraph. CONCLUSION: The low-cost, commercially- available wearable activity monitor (Movband) appears to provide a valid assessment of physical activity behavior in a free-living setting.

Effect of a Home-Based Exercise Intervention of Wearable Technology and Telephone Coaching on Walking Performance in Peripheral Artery Disease

Clinical practice guidelines support home-based exercise for patients with peripheral artery disease (PAD), but no randomized trials have tested whether an exercise intervention without periodic medical center visits improves walking performance. To determine whether a home-based exercise intervention consisting of a wearable activity monitor and telephone coaching improves walking ability over 9 months in patients with PAD. Randomized clinical trial conducted at 3 US medical centers. Patients with PAD were randomized between June 18, 2015, and April 4, 2017, to home-based exercise vs usual care for 9 months. Final follow-up was on December 5, 2017. The exercise intervention group (n = 99) received 4 weekly medical center visits during the first month followed by 8 months of a wearable activity monitor and telephone coaching. The usual care group (n = 101) received no onsite sessions, active exercise, or coaching intervention. The primary outcome was change in 6-minute walk distance at 9-month follow-up (minimal clinically important difference [MCID], 20 m). Secondary outcomes included 9-month change in subcomponents of the Walking Impairment Questionnaire (WIQ) (0-100 score; 100, best), SF-36 physical functioning score, Patient-Reported Outcomes Measurement Information System (PROMIS) mobility questionnaire (higher = better; MCID, 2 points), PROMIS satisfaction with social roles questionnaire, PROMIS pain interference questionnaire (lower = better; MCID range, 3.5-4.5 points), and objectively measured physical activity. Among 200 randomized participants (mean [SD] age, 70.2 [10.4] years; 105 [52.5%] women), 182 (91%) completed 9-month follow-up. The mean change from baseline to 9-month follow-up in the 6-minute walk distance was 5.5 m in the intervention group vs 14.4 m in the usual care group (difference, -8.9 m; 95% CI, -26.0 to 8.2 m; P = .31). The exercise intervention worsened the PROMIS pain interference score, mean change from baseline to 9 months was 0.7 in the intervention group vs -2.8 in the usual care group (difference, 3.5; 95% CI, 1.3 to 5.8; P = .002). There were no significant between-group differences in the WIQ score, the SF-36 physical functioning score, or the PROMIS mobility or satisfaction with social roles scores. Among patients with PAD, a home-based exercise intervention consisting of a wearable activity monitor and telephone coaching, compared with usual care, did not improve walking performance at 9-month follow-up. These results do not support home-based exercise interventions of wearable devices and telephone counseling without periodic onsite visits to improve walking performance in patients with PAD. clinicaltrials.gov Identifier: NCT02462824.

A semiparametric model for wearable sensor-based physical activity monitoring data with informative device wear.

Wearable sensors provide an exceptional opportunity in collecting real-time behavioral data in free living conditions. However, wearable sensor data from observational studies often suffer from information bias, since participants' willingness to wear the monitoring devices may be associated with the underlying behavior of interest. The aim of this study was to introduce a semiparametric statistical approach for modeling wearable sensor-based physical activity monitoring data with informative device wear. Our simulation study indicated that estimates from the generalized estimating equations showed ignorable bias when device wear patterns were independent of the participants physical activity process, but incrementally more biased when the patterns of device non-wear times were increasingly associated with the physical activity process. The estimates from the proposed semiparametric modeling approach were unbiased both when the device wear patterns were (i) independent or (ii) dependent to the underlying physical activity process. We demonstrate an application of this method using data from the 2003-2004 National Health and Nutrition Examination Survey ($N=4518$), to examine gender differences in physical activity measured using accelerometers. The semiparametric model can be implemented using our R package acc, free software developed for reading, processing, simulating, visualizing, and analyzing accelerometer data, publicly available at the Comprehensive R Archive Network.

Development of Wearable Physical Activity Monitoring System

Development of Wearable Physical Activity Monitoring System

The comfort, acceptability and accuracy of energy expenditure estimation from wearable ambulatory physical activity monitoring systems in soldiers

The comfort, acceptability and accuracy of energy expenditure estimation from wearable ambulatory physical activity monitoring systems in soldiers

An Adaptive Algorithm to Improve Energy Efficiency in Wearable Activity Recognition Systems

Activity recognition systems are used in rehabilitation centres to monitor activity of daily living in order to assess daily functional status of elderly. A low-cost, non-invasive, and continuous wearable activity monitoring system can be realized by one or multiple wearable sensor nodes to form a self-managing wireless medical body area network. There are several arising challenges essential to be dealt within developing wearable activity recognition systems, namely sensor node lifetime and detection accuracy. This paper investigates existing solutions, which address the key opposing challenges. We propose a feedback controller algorithm to dynamically adapt sampling rate for maintaining the tradeoff between the energy efficiency and accuracy. The Number of samples and transmitted data packets is the main sources of energy consumption that impacts the system accuracy. To validate the accuracy of our proposed algorithm, a public wearable activity recognition data set is constructed. The data set is collected from 20 healthy subjects over 7 activity types excluding the transition states, using up to four accelerometer sensors connected with IEEE 802.15.4 enabled nodes in our setup. Our proposed feedback controller algorithm nearly doubles the activity recognition system lifetime. This, in turn improves the users’ quality of experience by reducing the demand for battery replacements while the accuracy of detection is maintained at the same level.

Assessing performance status and clinical outcomes with wearable activity monitors.

6571 Background: Performance status (PS) is assessed to inform treatment decisions and predict outcomes in cancer. PS is often evaluated using ECOG or KPS scales, limited by their subjective and static nature. Wearable activity monitors provide oncologists with the opportunity to obtain continuous objective data on patients’ daily activity including steps, stairs climbed, and sleep. We evaluated the association between wearable activity monitor data, PS, and clinical outcomes. Methods: Patients with advanced cancer were enrolled in a prospective, observational study conducted at Cedars-Sinai Medical Center. Patients wore a Fitbit Charge HR for 3 consecutive clinic visits. ECOG/KPS were rated by treating physicians and serious adverse events (AE, clinically relevant grade 3+ by CTCAE v4), hospitalizations, and 6-month survival were collected. Correlations between PS and activity metrics were calculated. Multivariable regression models were fit to predict AEs and hospitalizations with activity data. The association between activity metrics and time to death was evaluated using survival analysis. Results: 35 patients (median age 62 years, 53% male) were evaluated. Most had gastrointestinal cancers (82%). Patients had ECOG PS of 0 (20%), 1 (40%), 2 (23%), and 3(17%). There were 10 (29%) pts with serious AEs, 14 (40%) hospitalizations, and 11 (31%) deaths. Average daily steps were significantly correlated with ECOG PS and KPS (r=0.73 and 0.70, respectively). Relationships between activity metrics, AEs, hospitalizations, and overall survival (OS) are displayed in the table below. Conclusions: We found a significant association between wearable activity monitor data and the risk of AEs, hospitalization and death. There is a strong correlation between step counts and KPS/ECOG PS. The potential of wearable activity data to predict outcomes and supplement PS assessment should be explored in future studies. Clinical trial information: NCT02659358. [Table: see text]

Correlating wearable activity monitor data with PROMIS detected distress and physical functioning in advanced cancer patients.

e21689 Background: Patients with advanced cancer experience significant distress. Timely identification and treatment of distress can improve outcomes and quality of life. Domains of distress (i.e. pain, fatigue, physical function) can be assessed using patient reported outcome (PRO) questionnaires. However, PROs can be burdensome to patients, particularly when performed serially. Given the relationship between physical activity and sleep with domains of distress, wearable activity monitors may assist in the real-time detection of distress in advanced cancer patients. Methods: We conducted a prospective, observational study at Cedars-Sinai Medical Center and enrolled patients with measurable stage 3+ cancer, ≥18yr, English speaking, ambulatory, with a smartphone, and prognosis of &gt; 3 months. Patients wore a Fitbit Charge HR continuously through 3 consecutive clinic visits, and completed NIH PROMIS tools (Physical Function, Pain, Sleep, Fatigue, and Emotional Distress) during visits. Fitbits recorded average daily step counts, stairs climbed, and sleep time. We conducted regression analyses that adjusted for baseline confounding variables and accounted for correlated responses. Results: 35 patients (Mean age 62; 53% males; 82% GI cancers) were evaluated. Patients had ECOG PS of 0 (20%), 1 (40%), 2 (23%), and 3(17%). The table below displays regression coefficients for steps, floors, and sleep in each PROMIS distress domain. Conclusions: There is a significant association between steps and floors climbed with multiple domains of distress and physical functioning. The lack of association between total sleep time and these PROs, may suggest that other metrics of sleep quality (i.e. awakenings), may be more relevant. These findings support further exploration of wearable data as a continuously monitored PRO surrogate in advanced cancer patients; wearable data should be further validated for use in both clinical and therapeutic trial settings. Clinical trial information: NCT02659358. [Table: see text]

Assessing the Impact of a Novel Smartphone Application Compared With Standard Follow-Up on Mobility of Patients With Knee Osteoarthritis Following Treatment With Hylan G-F 20: A Randomized Controlled Trial.

BackgroundOsteoarthritis (OA) is a leading cause of disability in the United States. Although no disease-modifying therapies exist, patients with knee OA who increase walking may reduce risk of functional limitations.ObjectiveThe objective of the study is to evaluate the impact of a mobile app (OA GO) plus wearable activity monitor/pedometer (Jawbone UP 24) used for 90 days on the mobility of patients with knee OA treated with hylan G-F 20.MethodsPatients with knee OA aged 30 to 80 years who were eligible to receive hylan G-F 20 and were familiar with smartphone technology were enrolled in this randomized, multicenter, open-label study. Patients who had a body mass index above 35 kg/m2 were excluded. All patients received a single 6-mL injection of hylan G-F 20 and wore the Jawbone monitor. The patients were then randomized 1:1 to Jawbone and OA GO (Group A; n=107) with visible feedback (unblinded) or Jawbone only (Group B; n=104) with no visible feedback (blinded). The primary endpoint was mean change from baseline in steps per day at day 90 between Groups A and B.ResultsBaseline characteristics were similar between groups. There were significant differences between the increases in least squares (LS) mean number of steps per day (1199 vs 467, P=.03) and the mean percentage change (35.8% vs 11.5%, P=.02) from baseline in favor of Group A over Group B. There was a greater reduction in pain from baseline during the 6-minute walk test in Group A versus Group B. (LS mean change: −55.3 vs −33.8, P=.007). Most patients (65.4%) and surveys of physicians (67.3%) reported they would be likely or very likely to use/recommend the devices. Patient Activity Measure-13 scores improved from baseline (LS mean change for Groups A and B: 5.0 vs 6.9), with no significant differences between groups. The occurrence of adverse events was similar in the 2 groups.ConclusionsUse of a novel smartphone app in conjunction with a wearable activity monitor provided additional improvement on mobility parameters such as steps per day and pain with walking in the 6-minute walk test in patients with knee OA who were treated with hylan G-F 20. Results also highlight the amenability of patients and physicians to using mobile health technology in the treatment of OA and suggest further study is warranted.

The Validity Of A Novel, Low-cost, Wearable Physical Activity Monitor In A Laboratory Setting

The Validity Of A Novel, Low-cost, Wearable Physical Activity Monitor In A Laboratory Setting

Measuring the impact of ambulatory red blood cell transfusion on home functional status: study protocol for a pilot randomized controlled trial

BackgroundRed blood cell (RBC) transfusion is frequently employed in both ambulatory and hospital environments with the aim of improving patient functional status. In the ambulatory setting, this practice is particularly common in patients with malignancy due to anemia associated with their cancer therapy. Increasingly, the efficacy of this US$10.5 billion per year practice has been called into question. While it is often standard of care for patients with chemotherapy-induced anemia to receive ambulatory RBC transfusions, it is unclear to what extent such transfusions affect home functional status. It is also unclear whether or not changes in functional status in this population can be objectively quantified using wearable activity monitors. We propose to directly measure the impact of outpatient RBC transfusions on at-home functional status by recording several physiological parameters and quantifiable physical activity metrics, e.g., daily energy expenditure and daily total step count, using the ActiGraph wGT3X-BT. This device is an accelerometer-based wearable activity monitor similar in size to a small watch and is worn at the waist. Study participants will wear the device during the course of their daily activities giving us quantifiable insight into activity levels in the home environment.Methods/designThis will be a randomized crossover pilot clinical trial with a participant study duration of 28 days. The crossover nature allows each patient to serve as their own control. Briefly, patients presenting at a tertiary medical center’s Ambulatory Infusion Center (AIC) will be randomized to either: (1) receive an RBC transfusion as scheduled (transfusion) or (2) abstain from the scheduled transfusion (no transfusion). After an appropriate washout period, participants will crossover from the transfusion arm to the no-transfusion arm or vice versa. Activity levels will be recorded continuously throughout the study using an accelerometry monitor. In addition to device data, functional status and health outcomes will be collected via a weekly telephone interview. The primary outcome measure will be daily energy expenditure. Performance metrics, such as step count changes, will also be evaluated. Additional secondary outcome measures will include daily sedentary time and Patient-reported Outcomes Measurement Information System (PROMIS) Global 10 Survey scores.DiscussionThis trial will provide important information on the feasibility and utility of using accelerometry monitors to directly assess the impact of RBC transfusion on patients’ functional status. The results of the study will inform the merit and methods of a more definitive future trial evaluating the impact of ambulatory RBC transfusions in the target population.Trial registrationClinicalTrials.gov, identifier: NCT02835937. Registered on 15 July 2016.

Feasibility and Acceptability of a Wearable Technology Physical Activity Intervention With Telephone Counseling for Mid-Aged and Older Adults: A Randomized Controlled Pilot Trial.

BackgroundAs adults age, their physical activity decreases and sedentary behavior increases, leading to increased risk of negative health outcomes. Wearable electronic activity monitors have shown promise for delivering effective behavior change techniques. However, little is known about the feasibility and acceptability of non-Fitbit wearables (Fitbit, Inc, San Francisco, California) combined with telephone counseling among adults aged more than 55 years.ObjectiveThe purpose of our study was to determine the feasibility, acceptability, and effect on physical activity of an intervention combining a wearable physical activity monitor, tablet device, and telephone counseling among adults aged 55-79 years.MethodsAdults (N=40, aged 55-79 years, body mass index=25-35, <60 min of activity per week) were randomized to receive a 12-week intervention or to a wait list control. Intervention participants received a Jawbone Up24 monitor, a tablet with the Jawbone Up app installed, and brief weekly telephone counseling. Participants set daily and weekly step goals and used the monitor’s idle alert to notify them when they were sedentary for more than 1 h. Interventionists provided brief counseling once per week by telephone. Feasibility was measured using observation and study records, and acceptability was measured by self-report using validated items. Physical activity and sedentary time were measured using ActivPAL monitors following standard protocols. Body composition was measured using dual-energy x-ray absorptiometry scans, and fitness was measured using a 6-min walk test.ResultsParticipants were 61.48 years old (SD 5.60), 85% (34/40) female, 65% (26/40) white. Average activity monitor wear time was 81.85 (SD 3.73) of 90 days. Of the 20 Up24 monitors, 5 were reported broken and 1 lost. No related adverse events were reported. Acceptability items were rated at least 4 on a scale of 1-5. Effect sizes for most outcomes were small, including stepping time per day (d=0.35), steps per day (d=0.26), sitting time per day (d=0.21), body fat (d=0.17), and weight (d=0.33).ConclusionsThe intervention was feasible and acceptable in this population. Effect sizes were similar to the sizes found using other wearable electronic activity monitors, indicating that when combined with telephone counseling, wearable activity monitors are a potentially effective tool for increasing physical activity and decreasing sedentary behavior.Trial registrationClinicaltrials.gov NCT01869348; https://clinicaltrials.gov/ct2/show/NCT01869348 (Archived by WebCite at http://www.webcitation.org/6odlIolqy)

Promise of Wearable Physical Activity Monitors in Oncology Practice.

Commercially available physical activity monitors provide clinicians an opportunity to obtain oncology patient health measures to an unprecedented degree. These devices can provide objective and quantifiable measures of physical activity, which are not subject to errors or bias of self-reporting or shorter duration of formal testing. Prior work on so-called quantified-self data was based on older-generation, research-grade accelerometers, which laid the foundation for consumer-based physical activity monitoring devices to be validated as a feasible and reliable tool in patients with cancer. Physical activity monitors are being used in chronic conditions including chronic obstructive pulmonary disease, congestive heart failure, diabetes mellitus, and obesity. Differing demographics, compounded with higher symptom and treatment burdens in patients with cancer, imply that additional work is needed to understand the unique strengths and weaknesses of physical activity monitors in this population. Oncology programs can systematically implement these tools into their workflows in an adaptable and iterative manner. Translating large amounts of data collected from an individual physical activity monitoring device into clinically relevant information requires sophisticated data compilation and reduction. In this article, we summarize the characteristics of older- and newer-generation physical activity monitors, review the validation of physical activity monitors with respect to health-related quality-of-life assessments, and describe the current role of these devices for the practicing oncologist. We also highlight the challenges and next steps needed for physical activity monitors to provide relevant information that can change the current state of oncology practice.