Wearable Activity Monitor Research Articles

A Home Telemedicine System for Continuous Respiratory Monitoring.

This article presents a continuous home telemonitoring system for chronic respiratory patients using 5G connectivity developed in partnership with Vodafone as a part of the 5G Trial in Milan established by the Italian Ministry of Economic Development. The system features a wearable respiratory and activity monitor, an environmental sensor and a pulse oximeter sending the data through a 5G router to a Multi-Edge Computing server, incorporated in the Vodafone 5G infrastructure, where they are stored and accessible for visualization. In particular, activity, respiratory and environmental data are continuously streamed and collected. The solution has been tested on 18 healthy volunteers during non-supervised recordings lasting at least 48 hours. The combination of recognized activities and associated respiratory parameters provided statistically significant variations in breathing patterns between one activity and the other, thus giving more complete information to the clinicians than previously studied telemedicine systems based on spot-checks. In particular, statistically significant differences are found in tidal volume and minute ventilation between horizontal and vertical postures (p < 0.001) and between vertical postures and dynamic activities (p < 0.001); the respiratory rate shows statistically significant differences between horizontal and vertical postures (p < 0.001). Some environmental parameters have different mean values between day and night, such as carbon dioxide (p < 0.001). Trials on patients are needed to further study this telemedicine solution and make it commercially available in the future. The main further technical development suggested is the use of commercial 5G smartphones as routers, in order to make the system usable outside of home settings.

Psychological and nutritional correlates of objectively assessed physical activity in patients with anorexia nervosa.

Physical activity (PA) plays a role in the course of anorexia nervosa (AN). To assess the association between PA, nutritional status and psychological parameters in patients with AN. Using a wearable activity monitor, PA was assessed in 60 female AN inpatients, by step count and time spent in 4 metabolic equivalent (MET)-intensity levels: sedentary behaviour, light, moderate and vigorous PA. In addition, BMI, psychological (patient-reported outcome questionnaires) and nutritional parameters (body fat, energy and macronutrient intake) were assessed. The study population spent little time in vigorous PA. BMI on admission and discharge was higher when more time was spent in sedentary behaviour, and lower with more time spent in light PA. Relationships between PA and patient-reported outcomes were weak and limited to an association between vigorous PA and compulsiveness. Low fat mass was associated with more time spent in light PA, while subjects with higher step counts showed less intake of energy, carbohydrates and fat. The relationship between inadequate food intake and increased PA in patients with AN requires further investigation.

Tracking Calories: Validity Of Wearable Activity Monitors

The use of commercially accessible activity monitors has increased over the past few years. Assessing the accuracy of these devices is necessary to inform recreational consumers about the validity of these products. PURPOSE: To assess the validity of four activity monitors (Monitor 1, Monitor 2, Monitor 3, and Monitor 4) for energy expenditure (EE) data. METHODS: Twenty-one subjects (8 male and 13 female), with an average age of 20.2 years performed three exercise protocols: walking at 3.0 mph, running at 6.0 mph, and a HIIT workout for ten minutes each. Each exercise bout was followed by a seated rest period until subjects returned to pre-exercise VO2 values. EE measured in kcal was collected from the Parvo metabolic cart and compared with the EE from four activity monitors. EE from activity monitors was recorded from apps in kilocalories (kcals) upon completion of the testing. Descriptive statistics were performed for all variables. Coefficient of determination (R2) was used to assess the validity of EE in kcals for all devices. RESULTS: Monitor 3 was the most accurate device with an R2 of 0.68 for walking, 0.62 for HIIT and 0.59 for running. Monitor 1 showed the weakest correlations for the running (0.27), and the HIIT (0.34) protocols but was comparable to Monitor 3 for walking (0.64). Monitor 2 was the least accurate for walking (R2 =0.246) and showed low validity for running and HIIT (0.36 and 0.47 respectively). Monitor 4 was most accurate for higher intensity activities such as running (0.68) and HIIT (0.67). CONCLUSION: Monitor 3 was consistently the most accurate out of tested devices. However, results of this study demonstrate inaccurate assessment of EE by all wearable devices. None of the activity monitors met the correlational standard of 0.7. Future research should continue to assess the validity of these devices to provide accurate information on various modalities and exercise intensities to recreational consumers.

Validation of a Wearable Accelerometer-Based Activity Monitor for Use in Future Osteoporosis Prevention Programs

Osteoporosis is considered a major public health problem worldwide. In order to develop effective physical exercise protocols for the prevention of osteoporosis and ensure skeletal integrity, the intensity of the exercise must be quantified objectively and accurately. This study aimed to assess the validity of a wearable accelerometer-based activity monitor for use in osteoporosis prevention programs. Eighteen premenopausal women completed an exercise protocol consisting of five countermovement jumps followed by four treadmill bouts at different speeds. Participants carried two pairs of accelerometers (Muvone® and ActiGraph GT3X+) located on the wrist and hip. Three types of analysis were performed: (1) association between measurements from both devices; (2) level of similarity in group estimates; and (3) evaluation of measurement bias. High to almost perfect correlations between the peak acceleration measured by both devices were found in all protocol tests (r = 0.607–0.975, p &lt; 0.001). Differences in group estimates were non-significant and measurement bias between devices was below 6%. In conclusion, the validity of Muvone® to quantify acceleration has been tested at both the wrist and hip and could be used to assess mechanical loading during physical activities for the implementation of population-wide osteoporosis prevention programs.

An Examination of the Relationship Between Motivation, Physical Activity, and Wearable Activity Monitor Use.

Wearable physical activity (PA) monitors are widely promoted as a means to motivate people to be more active, but the motivational profile of users has never been assessed. This study's purpose was to classify adult users by their motivational regulation scores and examine how these profiles were associated with moderate to vigorous PA (MVPA). Current users (N = 320) recruited across the United States completed a Web-based survey. Motivational regulations were measured using the Behavioral Regulation in Exercise Questionnaire, and associations with MVPA were explored using bivariate correlations. MVPA was more highly correlated with autonomous rather than controlling regulations. A cluster analysis was conducted using the respondents' motivational regulation scores. Five motivational profiles emerged from this analysis, and they differed significantly across motivation and MVPA scores. PA monitor users characterized by more autonomous motives presented with higher MVPA. As technology use increases, assessing the multidimensionality of PA monitor users' motivation may add value when researching PA behaviors.

Feasible but Not Yet Efficacious: A Scoping Review of Wearable Activity Monitors in Interventions Targeting Physical Activity, Sedentary Behavior, and Sleep.

The present review aimed to explore the range and characteristics of interventions that utilize WAM and descriptively summarize the efficacy of these interventions. A total of 65 articles (61 studies) were included in this review. Most of the WAM-based interventions (n=58) were designed to improve physical activity (PA). Interventions targeting sedentary behavior (SB) were much less common (n=12), and even less frequent were WAM-based sleep interventions (n=3). Most studies tested the feasibility of WAM-based interventions; hence, efficacy of these interventions in improving PA, SB, and/or sleep could not be conclusively determined. Nonetheless, WAM-based interventions showed considerable potential in increasing PA and decreasing SB. WAM-based PA interventions exhibited preliminary efficacy in increasing PA. Although not as many interventions were focused on SB, current interventions also showed potential in decreasing sedentary time. Meanwhile, more evidence is needed to determine the utility of WAM in improving sleep. Major challenges with including WAM as part of interventions are reduced engagement in using the devices over time and the rapid changes in technology resulting in devices becoming obsolete soon after completion of an efficacy trial.

Using a Wearable Activity Monitor to Accurately Measure Mobility After Surgery for Hip Fractures (MASH)-A Feasibility Study Protocol.

Introduction:Hip fractures are the most common reason for acute orthopaedic admission in the United Kingdom (UK) and pose a substantial cost to the National Health Service (NHS). A significant proportion of this expenditure is accounted for by hospital bed days, with additional contributions from health and social aftercare. Early ambulation following hip fracture surgery improves outcomes by accelerating functional recovery and reducing the need for ongoing care. The ability to track a patient’s rehabilitation is important in assessing their care needs. While this is challenging to assess accurately, doing so may help to further improve outcomes. The aim of this feasibility study is to determine whether it is possible to accurately measure Mobility After Surgery for Hip fractures (MASH) in the immediate post-operative period by tracking the frequency of mobilization, distance walked and overall activity in the first week following surgery using a wearable activity monitor, the activPAL device.Methods and Materials:A total of 50 patients will be recruited to participate in the study. Ethical approval was given to recruit patients with and without capacity to consent. Immediately after undergoing hip fracture surgery, a activPAL monitor weighing 9 grams and measuring 23.5 mm x 43 x 5 mm in size will be applied to the anterior aspect of the participants thigh with a standard adhesive dressing. We will be assessing the feasibility of using the activPALto measure mobility in this patient group.Discussion:The MASH study will contribute to the design and execution of the MASH trial, which will seek to assess the accuracy by which mobility can be measured following hip fracture surgery and how this information can best be used to improve rehabilitation and care.

Peace of mind: A community-industry-academic partnership to adapt dementia technology for Anishinaabe communities on Manitoulin Island.

IntroductionAging Technologies for Indigenous Communities in Ontario (ATICON) explores the technology needs of Anishinaabe older adults in the Manitoulin region of Northern Ontario. Our program of research addresses inequitable access to supportive technologies that may allow Indigenous older adults to successfully age in place.MethodsUsing Indigenous research methodologies (IRM) and community-based participatory research (CBPR) we explored the acceptability of CareBand - a wearable location and activity monitoring device for people living with dementia using a LoRaWAN, a low-power wide-area network technology. We conducted key informant consultations and focus groups with Anishinaabe Elders, formal and informal caregivers, and health care providers (n = 29) in four geographically distinct regions.ResultsOverall, participants agreed that CareBand would improve caregivers’ peace of mind. Our results suggest refinement of the technology is necessary to address the challenges of the rural geography and winter weather; to reconsider aesthetics; address privacy and access; and to consider the unique characteristics of Anishinaabe culture and reserve life.ConclusionAll three partners in this research, including the Indigenous communities, industry partner, and academic researchers, benefited from the use of CBPR and IRM. As CareBand is further developed, community input will be crucial for shaping a useful and valued device.

A Multimodal Wearable System for Continuous and Real-Time Breathing Pattern Monitoring During Daily Activity.

This study aims to understand breathing patterns during daily activities by developing a wearable respiratory and activity monitoring (WRAM) system. A novel multimodal fusion architecture is proposed to calculate the respiratory and exercise parameters and simultaneously identify human actions. A hybrid hierarchical classification (HHC) algorithm combining deep learning and threshold-based methods is presented to distinguish 15 complex activities for accuracy enhancement and fast computation. A series of signal processing algorithms are utilized and integrated to calculate breathing and motion indices. The designed wireless communication structure achieves the interactions among chest bands, mobile devices, and the data processing center. The advantage of the proposed HHC method is evaluated by comparing the average accuracy (97.22%) and predictive time (0.0094s) with machine learning and deep learning approaches. The nine breathing patterns during 15 activities were analyzed by investigating the data from 12 subjects. With 12 hours of naturalistic data collected from one participant, the WRAM system reports the breathing and exercise performance within the identified motions. The demonstration shows the ability of the WRAM system to monitor multiple users breathing and exercise status in real-time. The present system demonstrates the usefulness of the framework of breathing pattern monitoring during daily activities, which may be potentially used in healthcare. The proposed multimodal based WRAM system offers new insights into the breathing function of exercise in action and presents a novel approach for precision medicine and health state monitoring.

Study protocol for a sequential multiple assignment randomized trial (SMART) to improve physical activity in employed women

IntroductionPhysical activity monitors, motivational text messages, personal calls, and group meetings, have proven to be efficacious physical activity interventions. However, individual participant response to these interventions varies drastically. A SMART design (sequential multiple assignment randomized trial) provides an effective way to test interventions that start with an initial treatment and then transition to an augmented treatment for non-responders. We describe a SMART to determine the most effective adaptive intervention to increase physical activity (steps, moderate-to-vigorous physical activity) and improve cardiovascular health among employed women who are not regularly physically active. The SMART uses combinations of four treatments: 1) enhanced physical activity monitor (Fitbit wearable activity monitor and mobile app with goal setting and physical activity prescription), 2) text messages, 3) personal calls, and 4) group meetings. MethodsParticipants (N = 312) include women ages 18–70 employed at a large academic medical center. Women will be randomized to an initial intervention, either an enhanced physical activity monitor or enhanced physical activity monitor + text messaging. Non-responders to the initial intervention at 2 months will be randomized to either personal calls or groups meetings for the next 6 months. At 8 months, all participants will return to only an enhanced physical activity monitor until their final 12-month assessment. DiscussionResults of this study will add to the literature on improving physical activity in employed women. This study will identify effective interventions for women who respond to less intensive treatments, while maximizing benefits for those who need a more intensive approach.

ACTR-15. PHASE 1 TRIAL OF A KETOGENIC DIET IN PATIENTS RECEIVING STANDARD-OF-CARE TREATMENT FOR RECENTLY DIAGNOSED GLIOBLASTOMA

Abstract BACKGROUND There is abundant interest in the potential therapeutic and supportive role of a ketogenic diet (KD) in patients with glioblastoma (GBM). The KD is a high fat/low carbohydrate metabolic therapy that modulates several of the bioenergetic and biosynthetic pathways that are dysregulated in GBM. To date, studies of the KD in cancer patients have been limited in scope. This study will provide preliminary evidence on the safety and feasibility of a 16-week ketogenic diet in patients with GBM. METHODS This is an open-label single-arm feasibility trial being conducted at Cedars-Sinai Medical Center. We will recruit 20 recently diagnosed GBM patients who are receiving standard-of-care (SOC) treatment. Patients may enroll within 3 months of diagnosis, thus allowing patients who have already begun SOC chemoradiation the opportunity to participate. Excluded are patients with a KPS &lt; 70, BMI &lt; 22, or on high doses of steroids. Consenting patients will maintain a 16-week ketogenic diet (KD) supervised and monitored by study dietitians (RD). The primary outcome of safety will be assessed by monitoring weight, BMI, and adverse events. Secondary outcomes are: 1) Adherence to the KD, as assessed by BID blood glucose and ketone levels; 2) Time to progression and overall survival from date of KD initiation 3) Mean change in overall QOL, as measured using the QLQ30 and QLQ-BN20 questionnaires; and 4) Mean change in cognitive scores at 16 weeks from baseline. Exploratory outcomes include metabolic, inflammatory, and immune biomarkers; gut microbiota analysis; large oncosome analysis; and daily activity assessed with a wearable activity monitor. This novel trial incorporates multiple digital devices and mobile applications into the study design. Accrual is ongoing with 10 patients currently enrolled (NCT03451799).

Factors associated with long-term wearable physical activity monitor user engagement.

Wearable physical activity monitors (PAMs) have potential to positively influence physical activity. However, high rates of disengagement have been reported, which dampens enthusiasm, as these devices are unlikely to impact habitual physical activity if they are not worn for a sustained period of time. The purpose of this study was to identify demographic and device-use characteristics (e.g., data sharing) associated with sustained device engagement. Current PAM users (n = 418; mean age: 35.0 ± 12.5; 78% female) from across the USA were recruited online and completed a baseline web-based survey in 2015-2016 comprising questions about demographics and device use. Participants were followed-up again in 2017, at which time they reported whether or not they still used a PAM. Sustained PAM engagement was defined as those who continued use at follow-up. The median follow-up time was 15.5 (±3.7) months. In fully adjusted models, the following were significantly associated with long-term engagement: age (odds ratio [OR]: 1.03; 95% confidence interval [CI]: 1.01-1.05, p = .014), Hispanic ethnicity (OR: 3.67; 95% CI: 1.20-11.26, p = .023), running as a preferred exercise (OR: 1.82; 95% CI: 1.02-3.24, p = .043), wanting to monitor health variables as a reason for choosing to use a PAM (OR: 1.73; 95% CI: 1.02-2.92, p = .042), and sharing data from the PAM publicly on social media (e.g., Facebook and Twitter; OR: 5.11; 95% CI: 1.64-15.93, p = .005). A number of sociodemographic and use characteristics were associated with sustained device use over a median follow-up of 1.3 years. One modifiable factor that may lead to longer device engagement is encouraging users to share data publicly.

280 Tracking Physical Activity and Sleep Patterns in Emergency Medicine Residents Using Wearable Activity Monitors

There has been much attention and effort placed by the emergency medicine (EM) community on attempting to reduce resident and attending physician burnout and depression. Though the literature on EM wellness continues to grow, little is documented about the physical impact of the EM work schedule and lifestyle on a physician’s health and wellness. This prototype study was designed to better quantify some vital health indicators, and to define baseline physical activity and sleep patterns of EM residents. A secondary objective was to evaluate the feasibility, methodology and challenges associated with studies utilizing wearable activity monitoring technology. We conducted a single center, prospective, observational study of 25 EM residents. Subjects were 1st through 4th year EM residents who were asked to wear a Fitbit FlexTM activity monitor day and night for 14 days during an EM rotation. These residents work 9-10 hour shifts in a 400-bed community hospital that sees approximately 60,000 emergency department (ED) visits per year. Multiple baseline variables were measured including resident age, sex, post graduate level, body mass index (BMI), and marital and parental status. Activity and sleep variables included number of steps/day, steps/ED shift, and number of hours of sleep/day. Step and sleep data were excluded on days when Fitbit monitors were not worn, and a subject was excluded if the Fitbit was worn for less than 30% of the collection period. Categorical data were compared using the chi-square test for association. Between-group mean differences were compared by calculating t-tests for independent measures and analysis of variance. A p-value ≤0.05 (two-tail) was considered statistically significant. A total of 5,568 hours of Fitbit biometric data were collected and analyzed from our sample. Of the 25 subjects who enrolled in the study, 5 were excluded for not meeting the study inclusion criteria. Mean age of residents was 30 years old with a standard deviation (SD) of 2.5 years. 60% of the sample was male, 40% female, 35% married and 10% were parents. Average BMI for the entire group was 25.5 kg/m2 with a SD of 5.7 kg/m2. The mean total daily steps, the mean total steps taken per shift and mean total sleep per day are presented in Figure 1. Steps/day, steps/shift, sleep/day, and BMI were compared across all post graduate year levels and sex with no significant differences noted between these groups. This is only the third study to date to use wearable activity monitoring devices to measure the activity of emergency physicians and the first to create a biometric profile for the EM resident. We live in a time where this technology is accurate, minimally invasive, affordable and worn by many emergency physicians. There is an opportunity for future studies to replicate this design across subspecialties and in multiple centers in different geographical settings. Building biometric profiles that can be applied to any physician demographic group can provide great insight towards improving the health and wellness practices of busy and often overextended providers.

Feedback on Physical Activity Through a Wearable Device Connected to a Mobile Phone App in Patients With Metabolic Syndrome: Pilot Study.

BackgroundLittle is known of the effect of wearable devices on metabolic impairments in clinical settings. We hypothesized that a wearable device that can monitor and provide feedback on physical activity may help resolve metabolic syndrome.ObjectiveThis study aimed to examine the objective effects of the use of these devices on metabolic syndrome resolution.MethodsPatients diagnosed with metabolic syndrome were recruited. Participants were prescribed regular walking using a wearable device (Coffee WALKIE +Dv.3, GC Healthcare CI, Korea) on their wrist for 12 weeks. Participants received self-feedback on the amount of their exercise through an app on their mobile phone. The information on physical activities of the participants was uploaded automatically to a website. Thus, a trained nurse could provide individuals with feedback regarding the physical activity via telephone consultation on alternate weeks. Blood pressure (BP), body composition, fasting plasma glucose, and lipid profiles were recorded. The primary outcome was metabolic syndrome resolution. The secondary outcome was an improvement in the components of metabolic impairment.ResultsOf the 53 participants recruited, 20 participants with a median age of 46 (range 36-50) years completed the trial. There was no significant difference in the amount of calorie expenditure at weeks 4, 8, and 12. After 12 weeks, metabolic syndrome was resolved in 9 of 20 participants (45%), and the mean number of metabolic impairment components per person decreased from 3.4 to 2.9. Particularly, the mean systolic and diastolic BP decreased from mean 136.6 (SD 18.5) mm Hg to mean 127.4 (SD 19.5) mm Hg and from mean 84.0 (SD 8.1) mm Hg to mean 77.4 (SD 14.4) mm Hg (both P=.02), respectively.ConclusionsThis study found that a 12-week intervention via feedback, based on a wearable physical activity monitor, helped metabolic syndrome patients to be more engaged in regular walking and it improved impaired metabolic components, especially in BP. However, some practical challenges regarding patients’ adherence and sustained engagement were observed.

Wearable Activity Monitors as Part of a Childhood Obesity Treatment Program

PURPOSE: It is well known that childhood obesity has become a common issue in the United States (1), and that obesity contributes to a multitude of chronic diseases and negative health conditions (2). One of the biggest challenges in the treatment and prevention of childhood obesity is that the goal of these programs is primarily to modify behaviors that occur outside of the program space. The purpose of this study was to summarize the findings from a 6-month program that used wearable activity monitors (WAM) as part of a clinical obesity treatment program for fifteen children in Arizona (USA) between December 2015 to November 2017. METHODS: Obese children were referred to participate in this program by their pediatrician. Participants were provided a WAM that was used to monitor their physical activity (PA) levels, heart rate, and sleep habits. For the first week, participants were instructed not to change their behaviors so that baseline PA data could be collected. Subsequently, appropriate step and heart rate zone goals were set and progressively increased each week that a participant met their previous goal. RESULTS: Adherence to wearing the WAM was high, with only about 1.3% of activity data and 3% of sleep data missing throughout the entire program. Three children dropped out of the study before the program was completed. For the children who completed the program, modest improvements were noted for step count, and healthy sleep habits were found to be positively correlated with PA. In baseline data collection, the children walked on average 8,900 steps per day. In the final week, the children recorded 9,784 daily steps on average, representing approximately a 10% increase in the average number of steps taken. CONCLUSIONS: Overall, childhood obesity treatment programs focus heavily on modifying behaviors that occur outside of the clinic setting. A WAM appears to be a feasible approach to continuously monitor and increase the PA of obese children. Including WAM and progressive goal setting in a clinical obesity treatment program for children may be an effective method to increase PA levels outside of the clinical setting. Further exploration of the link between healthy sleep habits and PA could yield additional findings useful to childhood obesity treatment and prevention.

Does Sharing Wearable Physical Activity Monitor Data with Others Lead to Longer User Engagement?

Does Sharing Wearable Physical Activity Monitor Data with Others Lead to Longer User Engagement?

A Pilot Randomised Controlled Trial of a Text Messaging Intervention with Customisation Using Linked Data from Wireless Wearable Activity Monitors to Improve Risk Factors Following Gestational Diabetes.

Gestational diabetes (GDM) is a highly prevalent disorder of pregnancy which portends a high risk for future type 2 diabetes. Limited evidence indicates lifestyle intervention prevents the development of diabetes, but most previously studied interventions are resource-intensive. Intervention programs that utilise newer technologies may be scalable at lower cost. This 6-month pilot randomized controlled trial tested the delivery of text messages linked to an activity monitor, adaptive physical activity goal setting, and limited face-to-face counseling, as an intervention to improve rates of post-partum glucose tolerance testing and lifestyle behaviours amongst women following a GDM pregnancy. Sixty subjects were randomised 2:1 intervention vs. control. Compared to control subjects, there were trends for intervention subjects to improve diet, increase physical activity, and lose weight. There was no difference between the groups in the rate of glucose tolerance testing. Only 46 (77%) subjects completed some, and 19 subjects completed all the elements of the final evaluation. Feedback regarding the text messages and activity monitor was highly positive. Overall, results suggest that a text message and activity monitor intervention is feasible for a larger study or even as a potentially scalable population health intervention. However, low completion rates necessitate carefully considered modification of the protocol.

Improving Nutrition and Activity Behaviors Using Digital Technology and Tailored Feedback: Protocol for the Tailored Diet and Activity (ToDAy) Randomized Controlled Trial.

BackgroundExcess weight is a major risk factor for chronic diseases. In Australia, over 60% of adults are overweight or obese. The overconsumption of energy-dense nutrient-poor (EDNP) foods and low physical activity (PA) levels are key factors contributing to population obesity. New cost-effective approaches to improve population diet and PA behaviors are needed.ObjectiveThis 1-year randomized controlled trial (6-month intervention and 6-month follow-up) aims to investigate whether a tailored intervention using mobile technology can improve diet and PA behaviors leading to weight loss in adults (aged 18-65 years) who are overweight or obese and recruited through a social marketing campaign (LiveLighter).MethodsAll eligible participants will provide data on demographics and lifestyle behaviors online at baseline, 6 months, and 12 months. Using two-stage randomization, participants will be allocated into one of three conditions (n=200 per group): tailored feedback delivered via email at seven time points, informed by objective dietary (mobile food record app) and activity (wearable activity monitor) assessment; active control receiving no tailored feedback, but undergoing the same objective assessments as tailored feedback; and online control receiving no tailored feedback or objective assessments. Primary outcome measures at 6 and 12 months are changes in body mass, EDNP food and beverage consumption, and daily moderate-to-vigorous PA (measured via accelerometry). Secondary outcomes include change in fruit and vegetable consumption, daily sedentary behaviors, and cost effectiveness.ResultsEnrolment commenced in August 2017. Primary outcomes at 12 months will be available for analysis from September 2019.ConclusionsTailored email feedback provided to individuals may deliver a cost-effective strategy to overcome existing barriers to improving diet and PA. If found to be successful and cost effective, upscaling this intervention for inclusion in larger-scale interventions is highly feasible.Trial RegistrationAustralian New Zealand Clinical Trials Registry ACTRN12617000554369; https://www.anzctr.org.au /Trial/Registration/TrialReview.aspx?id=371325&isReview=trueInternational Registered Report Identifier (IRRID)DERR1-10.2196/12782

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

BackgroundClinical 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.ObjectiveThis 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.MethodsWe 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.ResultsThe 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.ConclusionsFunction 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.

Wearable Sweat Sensors: Background and Current Trends

AbstractSweat‐related physiology research has been well established over the years. However, it has only been around ten years that sweat‐based sensing devices started to be explored. With the recent advancements in wearable activity and physiology monitoring devices, sweat was investigated for its contents similar to blood and corresponding wearable devices were studied intensively. This article provides a thorough review on sweating mechanisms, sweat sensing devices, and electronic technologies for sweat sensor implementations. Potential future directions and recommendations based on current research trends were provided in each section. This review aims to offer a unique perspective from both physiology and engineering point‐of‐view to draw a complete landscape of the sweat sensing research.