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 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.

Universal phonon mean free path spectra in crystalline semiconductors at high temperature.

Thermal conductivity in non-metallic crystalline materials results from cumulative contributions of phonons that have a broad range of mean free paths. Here we use high frequency surface temperature modulation that generates non-diffusive phonon transport to probe the phonon mean free path spectra of GaAs, GaN, AlN, and 4H-SiC at temperatures near 80 K, 150 K, 300 K, and 400 K. We find that phonons with MFPs greater than 230 ± 120 nm, 1000 ± 200 nm, 2500 ± 800 nm, and 4200 ± 850 nm contribute 50% of the bulk thermal conductivity of GaAs, GaN, AlN, and 4H-SiC near room temperature. By non-dimensionalizing the data based on Umklapp scattering rates of phonons, we identified a universal phonon mean free path spectrum in small unit cell crystalline semiconductors at high temperature.