Wearable Sensor-Based Detection of Influenza in Presymptomatic and Asymptomatic Individuals.

BACKGROUND: The COVID-19 pandemic highlighted the need for early detection of viral infections in symptomatic and asymptomatic individuals to allow for timely clinical management and public health interventions. METHODS: Twenty healthy adults were challenged with an influenza A (H3N2) virus and prospectively monitored from 7 days before through 10 days after inoculation, using wearable electrocardiogram and physical activity sensors. This framework allowed for responses to be accurately referenced to the infection event. For each participant, we trained a semisupervised multivariable anomaly detection model on data acquired before inoculation and used it to classify the postinoculation dataset. RESULTS: Inoculation with this challenge virus was well-tolerated with an infection rate of 85%. With the model classification threshold set so that no alarms were recorded in the 170 healthy days recorded, the algorithm correctly identified 16 of 17 (94%) positive presymptomatic and asymptomatic individuals, on average 58 hours postinoculation and 23 hours before the symptom onset. CONCLUSIONS: The data processing and modeling methodology show promise for the early detection of respiratory illness. The detection algorithm is compatible with data collected from smartwatches using optical techniques but needs to be validated in large heterogeneous cohorts in normal living conditions. Clinical Trials Registration. NCT04204493.

Feasibility of combining biosensor and ecological momentary assessment to measure stress experiences among economically disadvantaged adolescents.

Adolescent stress is complex and impairing. Novel measures are needed to understand stress variability within individuals over time from a physiological as well as a subjective perspective. To test the feasibility of combining ecological momentary assessment (EMA) and wearable biosensors to assess adolescent stress, using an idiographic approach with experience sampling methods. A small sample (n = 23) of predominantly African American, economically disadvantaged adolescents were asked to complete EMA surveys four times per day and wear an armband measuring Heart rate (HR) and skin response for a 2-week period. Descriptive analyses examined number of hours of armband wear, percentage of viable data, and percentage of surveys completed by gender and race. Associations between biosensor data and EMA reports within and across individuals were also examined using hierarchical linear regression. EMA survey completion was good (81%) as was adherence to biosensor protocols, although technological difficulties interfered with collection of HR variability for youth with darker skin tones. Youth reported stressful events in 12.79% of EMA surveys, although 43% reported no negative mood experiences. Convergent validity was supported for detecting between-person (EMA) and within-person (EMA and biosensors) variability in stress across time, although associations across youth were highly variable. Results suggest value for biobehavioral methods in understanding day-to-day stress in adolescents but highlight variability in stress experiences as well as technological limitations, especially for youth of colour.

Cardiac-based detection of seizures in children with epilepsy.

INTRODUCTION: We evaluated a multi-parametric approach to seizure detection using cardiac and activity features to detect a wide range of seizures across different people using the same model. METHODS: Electrocardiogram (ECG) and accelerometer data were collected from a chest-worn sensor from 62 children aged 2-17 years undergoing video-electroencephalogram monitoring for clinical care. ECG data from 5 adults aged 31-48 years who experienced focal seizures were also analyzed from the PhysioNet database. A detection algorithm was developed based on a combination of multiple heart rhythm and motion parameters. RESULTS: Excluding patients with multiple seizures per hour and myoclonic jerks, 25 seizures were captured from 18 children. Using cardiac parameters only, 11/12 generalized seizures with clonic or tonic activity were detected as well as 7/13 focal seizures without generalization. Separately, cardiac parameters were evaluated using electrocardiogram data from 10 complex partial seizures in the PhysioNet database of which 7 were detected. False alarms averaged one per day. Movement-based parameters did not identify any seizures missed by cardiac parameters, but did improve detection time for 4 of the generalized seizures. CONCLUSION: Our data suggest that cardiac measures can detect seizures with bilateral motor features with high sensitivity, while detection of focal seizures depends on seizure duration and localization and may require customization of parameter thresholds.

Optimal design of an electrochemical reactor for blackwater treatment.

Electrolysis of blackwater for disinfection and nutrient removal is a portable and scalable technology that can lessen the need for cities to construct large-scale wastewater treatment infrastructure and enable the safe onsite reuse of blackwater. Several systems for treating wastewater from single toilets are described in the literature, but there are few examples of systems designed to use electrolysis to treat blackwater from nearby toilets, which is a situation more common in densely packed urban living environments. In order to scale a single toilet electrolysis system to one that could service multiple toilets, computational fluid dynamic analysis was used to optimize the electrochemical reactor design, and laboratory and field-testing were used to confirm results. Design efforts included optimization of the reactor shape and mixing to improve treatment efficiency, as well as automated cleaning and salt injection to reduce maintenance and service requirements. PRACTITIONER POINTS: Design of a reverse polarity mechanism to enable in situ electrode cleaning and improve long-term electrode performance. Optimization of a hopper design and drainpipe location to collect and remove flaking precipitates and mitigate maintenance issues. Design of an automated salt injection system to guarantee sufficient chloride levels for producing adequate chlorine residuals for consistent disinfection.

Resolving the relative contributions of cistern and pour flushing to toilet water usage: Measurements from urban test sites in India.

A challenge in water reuse for toilet flushing in India and other Asian countries derives from pour flushing practices. It is a common assumption that the amount of pour flushed water used for personal cleansing is small in comparison to the cistern flush volume, however there is a knowledge gap regarding the actual contribution of each water source to the blackwater amount. In this study, digital water meters were used to measure the fraction of water from personal wash tap relative to cistern water that is used for toilet flushing. High temporal resolution measurements were carried in three different urban sites in the city of Coimbatore in the southern Indian state of Tamil Nadu where onsite sanitation treatment prototypes that may provide reclaimed water for cistern flushing are being tested. Data collected over periods of up to 2 months show that the contribution of the cistern flush to the total blackwater volume is low (14-40%). These data highlight an important factor to inform interventions designed around water reuse for flushing in world geographies where personal toilet cleansing by water is the common practice.

Feasibility of Mild Traumatic Brain Injury Assessment Based on Cardiovascular Response to Postural Change.

OBJECTIVE: To determine the feasibility of short-term cardiovascular responses to postural change as a screening tool for mild traumatic brain injury (mTBI), using heart rate metrics that can be measured with a wearable electrocardiogram sensor. SETTING: Military TBI clinic. DESIGN: Data collected from active-duty service members who had sustained a medically diagnosed mTBI within the prior 72 hours and from age- and sex-matched controls. Cardiac data collected while participants performed a sequence of postural changes. MAIN MEASURES: Model classification compared with clinical mTBI diagnosis. RESULTS: Cardiac biomarkers of mTBI were identified and logistic regression classifiers for mTBI were developed from different subsets of biomarkers. The best model achieved 90% sensitivity and 69% specificity using data from 2 different postural changes. CONCLUSION: Noninvasive measurement of cardiovascular response to postural change is a promising approach for field-deployable post-mTBI screening.

An analysis of stereotypical motor movements and cardiovascular coupling in individuals on the autism spectrum.

One of the core diagnostic features of autism spectrum disorder (ASD) is engagement in stereotypical motor movements, although the etiology of this repetitive behavior is unknown. Since the 1960s, it has been hypothesized that stereotypical motor movements serve a homeostatic regulation function, and thereby a putative coupling mechanism to cardiovascular arousal. However, to date, surprisingly few reports explicitly assess cardio-somatic coupling and stereotypical motor movements. The present exploratory study investigates coupling of stereotypical body rocking and hand flapping to heart rate and heart rate variability (HRV) in a convenience sample (n = 10) of children and young adults with moderate to profound ASD. Motor movements were recorded via video and three-axis accelerometry, and simultaneous electrocardiographic signals were obtained to determine cardiovascular indices at or around the onset of naturalistically occurring stereotypy. Analysis of the heart rate revealed both repetitive body rocking and hand flapping in particular were found to associate with a strikingly similar cardiovascular pattern of acceleration and deceleration unrelated to physical demands associated with the movements themselves. Furthermore, neither type of stereotypical movement provoked directional change in heart rate variability. The implications of these results and opportunities for future research are discussed.

Soil-transmitted helminth eggs assessment in wastewater in an urban area in India.

Water quality and sanitation are inextricably linked to prevalence and control of soil-transmitted helminth infections, a public health concern in resource-limited settings. India bears a large burden of disease associated with poor sanitation. Transformative onsite sanitation technologies are being developed that feature elimination of pathogens including helminth eggs in wastewater treatment. We are conducting third-party testing of multiple sanitation technology systems in Coimbatore (Tamil Nadu) India. To ensure stringent testing of the pathogen removal ability of sanitation technologies, the presence of helminth eggs in wastewater across the town of Coimbatore was assessed. Wastewater samples from existing test sites as well as desludging trucks servicing residential and non-residential septic tanks, were collected. The AmBic methodology (based on washing, sieving, sedimenting and floating) was used for helminth egg isolation. We tested 29 different source samples and found a 52% prevalence of potentially infective helminth eggs. Identification and enumeration of helminth species is reported against the septage source (private residential vs. shared toilet facility) and total solids content. Trichuris egg counts were higher than those of hookworm and Ascaris from desludging trucks, whereas hookworm egg counts were higher in fresh wastewater samples. Surprisingly, no correlation between soil transmitted helminth eggs and total solids was observed.

Automated respiratory sinus arrhythmia measurement: Demonstration using executive function assessment.

Respiratory sinus arrhythmia (RSA) is a quantitative metric that reflects autonomic nervous system regulation and provides a physiological marker of attentional engagement that supports cognitive and affective regulatory processes. RSA can be added to executive function (EF) assessments with minimal participant burden because of the commercial availability of lightweight, wearable electrocardiogram (ECG) sensors. However, the inclusion of RSA data in large data collection efforts has been hindered by the time-intensive processing of RSA. In this study we evaluated the performance of an automated RSA-scoring method in the context of an EF study in preschool-aged children. The absolute differences in RSA across both scoring methods were small (mean RSA differences = -0.02-0.10), with little to no evidence of bias for the automated relative to the hand-scoring approach. Moreover, the relative rank-ordering of RSA across both scoring methods was strong (rs = .96-.99). Reliable changes in RSA from baseline to the EF task were highly similar across both scoring methods (96%-100% absolute agreement; Kappa = .83-1.0). On the basis of these findings, the automated RSA algorithm appears to be a suitable substitute for hand-scoring in the context of EF assessment.

Characterization of fecal sludge as biomass feedstock for thermal treatment in the southern Indian state of Tamil Nadu.

Background: Transformative sanitation technologies aim to treat fecal sludge (FS) by thermal processes and recover resources from it. There is a paucity of data describing the relevant properties of FS as viable feedstock for thermal treatment in major geographical target areas, such as India. Methods: This study characterized FS collected from septic tanks in two cities located in the Indian southern state of Tamil Nadu. FS samples were obtained at the point of discharge from trucks in Tiruppur (n=85 samples) and Coimbatore (n=50 samples). Additionally, biosolids obtained from sewage treatment plants (STP) in the cities of Coimbatore and Madurai were characterized. Total solids (TS) were measured, and proximate and ultimate analysis were conducted according to methods used by the fuel industry. Additionally, the ash content was analyzed for heavy metal using standard methods. Results: The average higher heating value (HHV) across all FS samples in Tiruppur (13.4 MJ/kg) was significantly higher than in Coimbatore (5.4 MJ/kg), which was partially attributed to the high ash content of 69% in the latter samples.  The HHV of the biosolids samples ranged from 10 to 12.2 MJ/Kg. The average total solids (TS) content for FS was 3.3% and 2.0% for Tiruppur and Coimbatore respectively, while the median TS content for the two cities was 2.3% and 1.2%. The heavy metal content of the ash was found to be below the thresholds for land disposal. Conclusions: This is one of the first studies that has systematically characterized the calorific and mineral content of septage and biosolids in several cities in India. We expect these data to serve as input data in the design of thermal processes for fecal sludge treatment.

Automated Detection of Repetitive Motor Behaviors as an Outcome Measurement in Intellectual and Developmental Disabilities.

Repetitive sensory motor behaviors are a direct target for clinical treatment and a potential treatment endpoint for individuals with intellectual or developmental disabilities. By removing the burden associated with video annotation or direct observation, automated detection of stereotypy would allow for longer term monitoring in ecologic settings. We report automated detection of common stereotypical motor movements using commercially available accelerometers affixed to the body and a generalizable detection algorithm. The method achieved a sensitivity of 80% for body rocking and 93% for hand flapping without individualized algorithm training or foreknowledge of subject's specific movements. This approach is well-suited for implementation in a continuous monitoring system outside of a clinical setting.

Biometrics and Policing: A Protocol for Multichannel Sensor Data Collection and Exploratory Analysis of Contextualized Psychophysiological Response During Law Enforcement Operations.

BACKGROUND: Stress experienced by law enforcement officers is often extreme and is in many ways unique among professions. Although past research on officer stress is informative, it is limited, and most studies measure stress using self-report questionnaires or observational studies that have limited generalizability. We know of no research studies that have attempted to track direct physiological stress responses in high fidelity, especially within an operational police setting. The outcome of this project will have an impact on both practitioners and policing researchers. To do so, we will establish a capacity to obtain complex, multisensor data; process complex datasets; and establish the methods needed to conduct idiopathic clinical trials on behavioral interventions in similar contexts. OBJECTIVE: The objective of this pilot study is to demonstrate the practicality and utility of wrist-worn biometric sensor-based research in a law enforcement agency. METHODS: We will use nonprobability convenience-based sampling to recruit 2-3 participants from the police department in Durham, North Carolina, USA. RESULTS: Data collection was conducted in 2016. We will analyze data in early 2017 and disseminate our results via peer reviewed publications in late 2017. CONCLUSIONS: We developed the Biometrics & Policing Demonstration project to provide a proof of concept on collecting biometric data in a law enforcement setting. This effort will enable us to (1) address the regulatory approvals needed to collect data, including human participant considerations, (2) demonstrate the ability to use biometric tracking technology in a policing setting, (3) link biometric data to law enforcement data, and (4) explore project results for law enforcement policy and training.