Recent Academic Research on Clinically Relevant Digital Measures: Systematic Review.

BACKGROUND: Digital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, ingestibles, and implantables are increasingly used by individuals and clinicians to capture health outcomes or behavioral and physiological characteristics of individuals. Although academia is taking an active role in evaluating digital sensing products, academic contributions to advancing the safe, effective, ethical, and equitable use of digital clinical measures are poorly characterized. OBJECTIVE: We performed a systematic review to characterize the nature of academic research on digital clinical measures and to compare and contrast the types of sensors used and the sources of funding support for specific subareas of this research. METHODS: We conducted a PubMed search using a range of search terms to retrieve peer-reviewed articles reporting US-led academic research on digital clinical measures between January 2019 and February 2021. We screened each publication against specific inclusion and exclusion criteria. We then identified and categorized research studies based on the types of academic research, sensors used, and funding sources. Finally, we compared and contrasted the funding support for these specific subareas of research and sensor types. RESULTS: The search retrieved 4240 articles of interest. Following the screening, 295 articles remained for data extraction and categorization. The top five research subareas included operations research (research analysis; n=225, 76%), analytical validation (n=173, 59%), usability and utility (data visualization; n=123, 42%), verification (n=93, 32%), and clinical validation (n=83, 28%). The three most underrepresented areas of research into digital clinical measures were ethics (n=0, 0%), security (n=1, 0.5%), and data rights and governance (n=1, 0.5%). Movement and activity trackers were the most commonly studied sensor type, and physiological (mechanical) sensors were the least frequently studied. We found that government agencies are providing the most funding for research on digital clinical measures (n=192, 65%), followed by independent foundations (n=109, 37%) and industries (n=56, 19%), with the remaining 12% (n=36) of these studies completely unfunded. CONCLUSIONS: Specific subareas of academic research related to digital clinical measures are not keeping pace with the rapid expansion and adoption of digital sensing products. An integrated and coordinated effort is required across academia, academic partners, and academic funders to establish the field of digital clinical measures as an evidence-based field worthy of our trust.

Assessing sedentary behavior with the GENEActiv: introducing the sedentary sphere.

BACKGROUND: The Sedentary Sphere is a method for the analysis, identification, and visual presentation of sedentary behaviors from a wrist-worn triaxial accelerometer. PURPOSE: This study aimed to introduce the concept of the Sedentary Sphere and to determine the accuracy of posture classification from wrist accelerometer data. METHODS: Three samples were used: 1) free living (n = 13, ages 20-60 yr); 2) laboratory based (n = 25, ages 30-65 yr); and 3) hospital inpatients (n = 10, ages 60-90 yr). All participants wore a GENEActiv on their wrist and activPAL on their thigh. The free-living sample wore an additional GENEActiv on the thigh and completed the Multimedia Activity Recall for Children and Adults. The laboratory-based sample wore the monitors while seated at a desk for 7 h, punctuated by 2 min of walking every 20 min. The free-living and inpatient samples wore the monitors for 24 h. Posture was classified from wrist-worn accelerometry using the Sedentary Sphere concept. RESULTS: Sitting time did not differ between the wrist GENEActiv and the activPAL in the free-living sample and was correlated in the three samples combined (rho = 0.9, P < 0.001), free-living and inpatient samples (r ≃ 0.8, P < 0.01). Mean intraindividual agreement was 85% ± 7%. In the laboratory-based and inpatient samples, sitting time was underestimated by the wrist GENEActiv by 30 min and 2 h relative to the activPAL, respectively (P < 0.05). Posture classification disagreed during reading while standing, cooking while standing, and brief periods during driving. Posture allocation validity was excellent when the GENEActiv was worn on the thigh, evidenced by the near-perfect agreement with the activPAL (96% ± 3%). CONCLUSIONS: The Sedentary Sphere enables determination of the most likely posture from the wrist-worn GENEActiv. Visualizing behaviors on the sphere displays the pattern of wrist movement and positions within that behavior.

Effect of short-term reduced physical activity on cardiovascular risk factors in active lean and overweight middle-aged men.

OBJECTIVES: An experimental reduction in physical activity is a useful tool for exploring the health benefits of physical activity. This study investigated whether similarly-active overweight men show a more pronounced response to reduced physical activity than their lean counterparts because of their atherogenic phenotype (i.e., greater abdominal adiposity). METHODS: From 115 active men aged 45-64years, we recruited nine active lean (waist circumference <84cm) and nine active central overweight men (waist circumference >94cm). Fasting blood samples and responses to an oral glucose tolerance test (OGTT) were measured at baseline and following one week of reduced physical activity to simulate sedentary levels (removal of structured exercise and reduced habitual physical activity). RESULTS: Glucose and insulin areas under the curve (AUC), CRP, ALT, TAG were all higher in the overweight group and remained so throughout (P<0.05). Insulin and glucose AUC responses to an OGTT, as well as fasting triglyceride (TAG) concentrations, increased in both groups as a result of the intervention (P<0.05). There was no change in interleukin-6, C-reactive protein (CRP), Tumour Necrosis Factor-α, soluble intracellular adhesion molecule 1, or alanine transaminase (ALT). CONCLUSION: One-week of reduced activity similarly-impaired glucose control and increased fasting TAG in both lean and overweight men. Importantly, in spite of very similar (high) levels of habitual physical activity, central overweight men displayed a poorer profile for various inflammatory and metabolic outcomes (CRP, ALT, TAG, glucose AUC and insulin AUC).

Physical activity classification using the GENEA wrist-worn accelerometer.

INTRODUCTION: Most accelerometer-based activity monitors are worn on the waist or lower back for assessment of habitual physical activity. Output is in arbitrary counts that can be classified by activity intensity according to published thresholds. The purpose of this study was to develop methods to classify physical activities into walking, running, household, or sedentary activities based on raw acceleration data from the GENEA (Gravity Estimator of Normal Everyday Activity) and compare classification accuracy from a wrist-worn GENEA with a waist-worn GENEA. METHODS: Sixty participants (age = 49.4 ± 6.5 yr, body mass index = 24.6 ± 3.4 kg·m⁻²) completed an ordered series of 10-12 semistructured activities in the laboratory and outdoor environment. Throughout, three GENEA accelerometers were worn: one at the waist, one on the left wrist, and one on the right wrist. Acceleration data were collected at 80 Hz. Features obtained from both fast Fourier transform and wavelet decomposition were extracted, and machine learning algorithms were used to classify four types of daily activities including sedentary, household, walking, and running activities. RESULTS: The computational results demonstrated that the algorithm we developed can accurately classify certain types of daily activities, with high overall classification accuracy for both waist-worn GENEA (0.99) and wrist-worn GENEA (right wrist = 0.97, left wrist = 0.96). CONCLUSIONS: We have successfully developed algorithms suitable for use with wrist-worn accelerometers for detecting certain types of physical activities; the performance is comparable to waist-worn accelerometers for assessment of physical activity.

Markers of chronic inflammation with short-term changes in physical activity.

PURPOSE: Regular exercise is inversely related to markers of chronic inflammation, but we do not know to what extent these changes are the product of recent exercise behavior. The aim of the present investigation was to examine the stability of markers of chronic inflammation in the face of short-term positive and negative changes in physical activity in middle-aged men. METHODS: Two studies were conducted using a randomized counterbalanced design. In the first study (Study 1), eight highly active men (age = 56 ± 5 yr, body mass index (BMI) = 23.3 ± 3.2 kg·m(-2), VO(2max) = 50.7 ± 7.0 mL·kg(-1)·min(-1)) undertook two trials; withdrawal of exercise for 1 wk versus control (normal exercise behavior). In the second study (Study 2), 10 sedentary men (age = 57 ± 2 yr, BMI = 27.9 ± 3.6 kg·m(-2), VO(2max) = 30.4 ± 4.6 mL·kg(-1)·min(-1)) undertook 30 min of daily walking at 60% VO(2max) for 1 wk versus control (normal sedentary behavior). RESULTS: The withdrawal of exercise for 1 wk in highly active men (Study 1) and the imposition of 1 wk of daily exercise in sedentary men (Study 2) did not elicit any substantial changes in the inflammatory proteins C-reactive protein (CRP), IL-6, and TNF-α and circulating leukocyte concentration. The differences in inflammatory proteins between active (Study 1) and sedentary (Study 2) men were marked; for example, baseline CRP was 0.85 ± 0.79 and 3.02 ± 2.30 mg·L(-1), respectively. CONCLUSIONS: The inflammatory markers CRP, IL-6, and TNF-α are stable and not affected by large short-term positive or negative alterations in exercise behavior. This stability strengthens the use of these markers in clinical and research settings because differences and changes are not simply the product of recent exercise behavior.

Validation of the GENEA Accelerometer.

PURPOSE: The study aims were: 1) to assess the technical reliability and validity of the GENEA using a mechanical shaker; 2) to perform a GENEA value calibration to develop thresholds for sedentary and light-, moderate-, and vigorous-intensity physical activity; and 3) to compare the intensity classification of the GENEA with two widely used accelerometers. METHODS: A total of 47 GENEA accelerometers were attached to a shaker and vertically accelerated, generating 15 conditions of varying acceleration and/or frequency. Reliability was calculated using SD and intrainstrument and interinstrument coefficients of variation, whereas validity was assessed using Pearson correlation with the shaker acceleration as the criterion. Next, 60 adults wore a GENEA on each wrist and on the waist (alongside an ActiGraph and RT3 accelerometer) while completing 10-12 activity tasks. A portable metabolic gas analyzer provided the criterion measure of physical activity. Analyses involved the use of Pearson correlations to establish criterion and concurrent validity and receiver operating characteristic curves to establish intensity cut points. RESULTS: The GENEA demonstrated excellent technical reliability (CVintra = 1.4%, CVinter = 2.1%) and validity (r = 0.98, P < 0.001) using the mechanical shaker. The GENEA demonstrated excellent criterion validity using VO2 as the criterion (left wrist, r = 0.86; right wrist, r = 0.83; waist, r = 0.87), on par with the waist-worn ActiGraph and RT3. The GENEA demonstrated excellent concurrent validity compared with the ActiGraph (r = 0.92) and the RT3 (r = 0.97). The waist-worn GENEA had the greatest classification accuracy (area under the receiver operating characteristic curve (AUC) = 0.95), followed by the left (AUC = 0.93) and then the right wrist (AUC = 0.90). The accuracy of the waist-worn GENEA was virtually identical with that of the ActiGraph (AUC = 0.94) and RT3 (AUC = 0.95). CONCLUSION: The GENEA is a reliable and valid measurement tool capable of classifying the intensity of physical activity in adults.

Oxidative stress, inflammation and recovery of muscle function after damaging exercise: effect of 6-week mixed antioxidant supplementation.

There is no consensus regarding the effects of mixed antioxidant vitamin C and/or vitamin E supplementation on oxidative stress responses to exercise and restoration of muscle function. Thirty-eight men were randomly assigned to receive either placebo group (n = 18) or mixed antioxidant (primarily vitamin C & E) supplements (n = 20) in a double-blind manner. After 6 weeks, participants performed 90 min of intermittent shuttle-running. Peak isometric torque of the knee flexors/extensors and range of motion at this joint were determined before and after exercise, with recovery of these variables tracked for up to 168 h post-exercise. Antioxidant supplementation elevated pre-exercise plasma vitamin C (93 ± 8 µmol l(-1)) and vitamin E (11 ± 3 µmol l(-1)) concentrations relative to baseline (P < 0.001) and the placebo group (P ≤ 0.02). Exercise reduced peak isometric torque (i.e. 9-19% relative to baseline; P ≤ 0.001), which persisted for the first 48 h of recovery with no difference between treatment groups. In contrast, changes in the urine concentration of F(2)-isoprostanes responded differently to each treatment (P = 0.04), with a tendency for higher concentrations after 48 h of recovery in the supplemented group (6.2 ± 6.1 vs. 3.7 ± 3.4 ng ml(-1)). Vitamin C & E supplementation also affected serum cortisol concentrations, with an attenuated increase from baseline to the peak values reached after 1 h of recovery compared with the placebo group (P = 0.02) and serum interleukin-6 concentrations were higher after 1 h of recovery in the antioxidant group (11.3 ± 3.4 pg ml(-1)) than the placebo group (6.2 ± 3.8 pg ml(-1); P = 0.05). Combined vitamin C & E supplementation neither reduced markers of oxidative stress or inflammation nor did it facilitate recovery of muscle function after exercise-induced muscle damage.

Active middle-aged men have lower fasting inflammatory markers but the postprandial inflammatory response is minimal and unaffected by physical activity status.

Physical activity modifies some postprandial responses such as glycemic control, although it is unclear whether this translates into lower postprandial inflammation. Our objective in this study was to determine whether postprandial inflammatory markers are lower in active compared with sedentary middle-aged men. Thirteen active and twelve sedentary middle-aged men consumed a mixed meal on one occasion. Blood was taken via a cannula before and up to 8 h after the meal and with a single-use needle before and 8 h after the meal. Active men had lower fasted IL-6 (0.6 +/- 0.2 vs. 1.2 +/- 0.3 pg/ml; P = 0.004) and C-reactive protein (1.3 +/- 0.3 vs. 2.9 +/- 0.6 mg/l; P = 0.04) concentrations than sedentary men. Cannula blood IL-6 concentrations increased by 3.49 pg/ml in the 8 h following the meal (P < 0.001); however, this increase was minimal (0.36 pg/ml) in blood taken via a single-use needle from the contralateral arm (P = 0.013). The sedentary group had larger glucose (P = 0.034), insulin (P = 0.013), and triacylglycerol (P = 0.057) responses to the meal. These results provide further evidence that physical activity is associated with lower inflammatory marker concentrations in a fasted state and a lower postprandial metabolic response to a meal. However, this does not translate into lower postprandial inflammatory markers since the only evidence of postprandial inflammation (a large increase in serum IL-6) was actually due to the cannula used for blood sampling.

Rates and determinants of uptake and use of an internet physical activity and weight management program in office and manufacturing work sites in England: cohort study.

BACKGROUND: Internet-based physical activity (PA) and weight management programs have the potential to improve employees' health in large occupational health settings. To be successful, the program must engage a wide range of employees, especially those at risk of weight gain or ill health. OBJECTIVE: The aim of the study was to assess the use and nonuse (user attrition) of a Web-based and monitoring device-based PA and weight management program in a range of employees and to determine if engagement with the program was related to the employees' baseline characteristics or measured outcomes. METHODS: Longitudinal observational study of a cohort of employees having access to the MiLife Web-based automated behavior change system. Employees were recruited from manufacturing and office sites in the North West and the South of England. Baseline health data were collected, and participants were given devices to monitor their weight and PA via data upload to the website. Website use, PA, and weight data were collected throughout the 12-week program. RESULTS: Overall, 12% of employees at the four sites (265/2302) agreed to participate in the program, with 130 men (49%) and 135 women (51%), and of these, 233 went on to start the program. During the program, the dropout rate was 5% (11/233). Of the remaining 222 Web program users, 173 (78%) were using the program at the end of the 12 weeks, with 69% (153/222) continuing after this period. Engagement with the program varied by site but was not significantly different between the office and factory sites. During the first 2 weeks, participants used the website, on average, 6 times per week, suggesting an initial learning period after which the frequency of website log-in was typically 2 visits per week and 7 minutes per visit. Employees who uploaded weight data had a significant reduction in weight (-2.6 kg, SD 3.2, P< .001). The reduction in weight was largest for employees using the program's weight loss mode (-3.4 kg, SD 3.5). Mean PA level recorded throughout the program was 173 minutes (SE 12.8) of moderate/high intensity PA per week. Website interaction time was higher and attrition rates were lower (OR 1.38, P= .03) in those individuals with the greatest weight loss. CONCLUSIONS: This Web-based PA and weight management program showed high levels of engagement across a wide range of employees, including overweight or obese workers, shift workers, and those who do not work with computers. Weight loss was observed at both office and manufacturing sites. The use of monitoring devices to capture and send data to the automated Web-based coaching program may have influenced the high levels of engagement observed in this study. When combined with objective monitoring devices for PA and weight, both use of the website and outcomes can be tracked, allowing the online coaching program to become more personalized to the individual.

Using internet and mobile phone technology to deliver an automated physical activity program: randomized controlled trial.

BACKGROUND: The Internet has potential as a medium for health behavior change programs, but no controlled studies have yet evaluated the impact of a fully automated physical activity intervention over several months with real-time objective feedback from a monitor. OBJECTIVE: The aim was to evaluate the impact of a physical activity program based on the Internet and mobile phone technology provided to individuals for 9 weeks. METHODS: A single-center, randomized, stratified controlled trial was conducted from September to December 2005 in Bedfordshire, United Kingdom, with 77 healthy adults whose mean age was 40.4 years (SD = 7.6) and mean body mass index was 26.3 (SD = 3.4). Participants were randomized to a test group that had access to an Internet and mobile phone-based physical activity program (n = 47) or to a control group (n = 30) that received no support. The test group received tailored solutions for perceived barriers, a schedule to plan weekly exercise sessions with mobile phone and email reminders, a message board to share their experiences with others, and feedback on their level of physical activity. Both groups were issued a wrist-worn accelerometer to monitor their level of physical activity; only the test group received real-time feedback via the Internet. The main outcome measures were accelerometer data and self-report of physical activity. RESULTS: At the end of the study period, the test group reported a significantly greater increase over baseline than did the control group for perceived control (P < .001) and intention/expectation to exercise (P < .001). Intent-to-treat analyses of both the accelerometer data (P = .02) and leisure time self-report data (P = .03) found a higher level of moderate physical activity in the test group. The average increase (over the control group) in accelerometer-measured moderate physical activity was 2 h 18 min per week. The test group also lost more percent body fat than the control group (test group: -2.18, SD = 0.59; control group: -0.17, SD = 0.81; P = .04). CONCLUSIONS: A fully automated Internet and mobile phone-based motivation and action support system can significantly increase and maintain the level of physical activity in healthy adults.