User-centered design of feedback regarding health-related behaviors derived from wearables: An approach targeting older adults and persons living with neurodegenerative disease.

Objective: There has been tremendous growth in wearable technologies for health monitoring but limited efforts to optimize methods for sharing wearables-derived information with older adults and clinical cohorts. This study aimed to co-develop, design and evaluate a personalized approach for information-sharing regarding daily health-related behaviors captured with wearables. Methods: A participatory research approach was adopted with: (a) iterative stakeholder, and evidence-led development of feedback reporting; and (b) evaluation in a sample of older adults (n = 15) and persons living with neurodegenerative disease (NDD) (n = 25). Stakeholders included persons with lived experience, healthcare providers, health charity representatives and individuals involved in aging/NDD research. Feedback report information was custom-derived from two limb-mounted inertial measurement units and a mobile electrocardiography device worn by participants for 7-10 days. Mixed methods were used to evaluate reporting 2 weeks following delivery. Data were summarized using descriptive statistics for the group and stratified by cohort and cognitive status. Results: Participants (n = 40) were 60% female (median 72 (60-87) years). A total of 82.5% found the report easy to read or understand, 80% reported the right amount of information was shared, 90% found the information helpful, 92% shared the information with a family member or friend and 57.5% made a behavior change. Differences emerged in sub-group comparisons. A range of participant profiles existed in terms of interest, uptake and utility. Conclusions: The reporting approach was generally well-received with perceived value that translated into enhanced self-awareness and self-management of daily health-related behaviors. Future work should examine potential for scale, and the capacity for wearables-derived feedback to influence longer-term behavior change.

Detecting accelerometer non-wear periods using change in acceleration combined with rate-of-change in temperature.

BACKGROUND: Accelerometery is commonly used to estimate physical activity, sleep, and sedentary behavior. In free-living conditions, periods of device removal (non-wear) can lead to misclassification of behavior with consequences for research outcomes and clinical decision making. Common methods for non-wear detection are limited by data transformations (e.g., activity counts) or algorithm parameters such as minimum durations or absolute temperature thresholds that risk over- or under-estimating non-wear time. This study aimed to advance non-wear detection methods by integrating a 'rate-of-change' criterion for temperature into a combined temperature-acceleration algorithm. METHODS: Data were from 39 participants with neurodegenerative disease (36% female; age: 45-83 years) who wore a tri-axial accelerometer (GENEActiv) on their wrist 24-h per day for 7-days as part of a multi-sensor protocol. The reference dataset was derived from visual inspection conducted by two expert analysts. Linear regression was used to establish temperature rate-of-change as a criterion for non-wear detection. A classification and regression tree (CART) decision tree classifier determined optimal parameters separately for non-wear start and end detection. Classifiers were trained using data from 15 participants (38.5%). Outputs from the CART analysis were supplemented based on edge cases and published parameters. RESULTS: The dataset included 186 non-wear periods (85.5% < 60 min). Temperature rate-of-change over the first five minutes of non-wear was - 0.40 ± 0.17 °C/minute and 0.36 ± 0.21 °C/minute for the first five minutes following device donning. Performance of the DETACH (DEvice Temperature and Accelerometer CHange) algorithm was improved compared to existing algorithms with recall of 0.942 (95% CI 0.883 to 1.0), precision of 0.942 (95% CI 0.844 to 1.0), F1-Score of 0.942 (95% CI 0.880 to 1.0) and accuracy of 0.996 (0.994-1.000). CONCLUSION: The DETACH algorithm accurately detected non-wear intervals as short as five minutes; improving non-wear classification relative to current interval-based methods. Using temperature rate-of-change combined with acceleration results in a robust algorithm appropriate for use across different temperature ranges and settings. The ability to detect short non-wear periods is particularly relevant to free-living scenarios where brief but frequent removals occur, and for clinical application where misclassification of behavior may have important implications for healthcare decision-making.

Standing, Transition, and Walking Ability in Older Adults: The Case for Independently Evaluating Different Domains of Mobility Function.

BACKGROUND: Independent mobility is a complex behavior that relies on the ability to walk, maintain stability, and transition between postures. However, guidelines for assessment that details what elements of mobility to evaluate and how they should be measured remain unclear. METHODS: Performance on tests of standing, sit-to-stand, and walking were evaluated in a cohort of 135 complex, comorbid, and older adults (mean age 87 ± 5.5 years). Correlational analysis was conducted to examine the degree of association for measures within and between mobility domains on a subset of participants (n = 83) able to complete all tasks unaided. Participants were also grouped by the presence of risk markers for frailty (gait speed and grip strength) to determine if the level of overall impairment impacted performance scores and if among those with risk markers, the degree of association was greater. RESULTS: Within-domain relationships for sit-to-stand and walking were modest (rho = 0.01-0.60). Associations either did not exist or relationships were weak for measures reflecting different domains (rho = -0.35 to 0.25, p > 0.05). As expected, gait speed differed between those with and without frailty risk markers (p < 0.001); however, balance and sit-to-stand measures did not (p ≥ 0.05). CONCLUSIONS: This study highlights the need to independently evaluate different mobility domains within an individual as a standard assessment approach. Modest within-domain relationships emphasize the need to account for multiple, unique control challenges within more complex domains. These findings have important implications for standardized mobility assessment and targeted rehabilitation strategies for older adults.

Feasibility of a continuous, multi-sensor remote health monitoring approach in persons living with neurodegenerative disease.

BACKGROUND: Remote health monitoring with wearable sensor technology may positively impact patient self-management and clinical care. In individuals with complex health conditions, multi-sensor wear may yield meaningful information about health-related behaviors. Despite available technology, feasibility of device-wearing in daily life has received little attention in persons with physical or cognitive limitations. This mixed methods study assessed the feasibility of continuous, multi-sensor wear in persons with cerebrovascular (CVD) or neurodegenerative disease (NDD). METHODS: Thirty-nine participants with CVD, Alzheimer's disease/amnestic mild cognitive impairment, frontotemporal dementia, Parkinson's disease, or amyotrophic lateral sclerosis (median age 68 (45-83) years, 36% female) wore five devices (bilateral ankles and wrists, chest) continuously for a 7-day period. Adherence to device wearing was quantified by examining volume and pattern of device removal (non-wear). A thematic analysis of semi-structured de-brief interviews with participants and study partners was used to examine user acceptance. RESULTS: Adherence to multi-sensor wear, defined as a minimum of three devices worn concurrently, was high (median 98.2% of the study period). Non-wear rates were low across all sensor locations (median 17-22 min/day), with significant differences between some locations (p = 0.006). Multi-sensor non-wear was higher for daytime versus nighttime wear (p < 0.001) and there was a small but significant increase in non-wear over the collection period (p = 0.04). Feedback from de-brief interviews suggested that multi-sensor wear was generally well accepted by both participants and study partners. CONCLUSION: A continuous, multi-sensor remote health monitoring approach is feasible in a cohort of persons with CVD or NDD.

Gene expression profiles for cell wall-modifying proteins associated with soybean cyst nematode infection, petiole abscission, root tips, flowers, apical buds, and leaves.

Changes in transcript accumulation for cell wall-modifying proteins were examined in excised soybean root pieces colonized by soybean cyst nematodes (SCN), Heterodera glycines, using RT-PCR and soybean Affymetrix GeneChips. Sequence-specific PCR primer pairs were prepared from sequence data for core sequences in the GenBank soybean database and consensus sequences derived from the assembly of soybean ESTs. In addition, to identify previously uncharacterized soybean transcripts, degenerate primers were prepared for conserved motifs in cellulases (endo-1,4-beta-glucanases, EGases) and polygalacturonases (PGs) and these were used to amplify segments of transcripts that were then extended with 3' and 5' RACE. Several novel EGase and PG transcripts were identified. Gene expression patterns were determined by real-time RT-PCR for 11 EGases, three expansins (EXPs), 14 PGs, two pectate lyases (PLs), and two xyloglucan endotransglucosylase/hydrolases (XTHs) in soybean roots inoculated with SCN, non-inoculated roots, serial dissections of root tips, leaf abscission zones, flowers, apical buds, and expanding leaves. A large number of genes associated with cell wall modifications are strongly up-regulated in root pieces colonized by SCN. However, in contrast to most of the transcripts for cell wall proteins, two XTH transcripts were specifically down-regulated in the colonized root pieces. Gene expression in serial dissections of root tips (0-2 mm, and 2-7 mm) and whole roots indicate that the SCN up-regulated genes are associated with a wide range of developmental processes in roots. Also of interest, many of the cDNAs examined were up-regulated in petiole abscission zones induced to abscise with ethylene.

Characterization of Several Heterodera glycines mRNA that Encode Small Proteins with Putative Signal Peptides.

Two subtraction libraries were prepared from RNA extracted at early and late stages in the development of soybean cyst nematodes (SCN), Heterodera glycines, in soybean roots. The cDNA from inoculated roots were subtracted with cDNA prepared from non-inoculated roots and SCN eggs, and 384 clones from each library were sequenced. BLAST searches revealed that 191 of the cDNA in the late library were most probably of nematode origin. Alignment of the 191 sequences produced 28 unigenes and 1 singlet. The size of the transcripts for the nematode genes was confirmed by RNA blot hybridization. Thirteen SCN transcripts were selected for further study because they included short open reading frames encoding predicted proteins of <20 kDa with signal peptides at their amino-terminus. Ten of the 13 encode predicted peptides <10 kDa. Although most of the 13 transcripts were fairly abundant in the SCN dbEST, most were of unknown function based on BLAST similarities. Nevertheless, several had characteristics common to anti-microbial peptides, and in situ hybridization indicated that three of the selected transcripts were expressed in the female reproductive system.