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Accurate assessment of pacemaker function or malfunction is essential to make clinical interpretations on pacemaker therapy and patient symptoms. This article presents an innovative approach for detecting pacemaker pulses at sampling frequency as low as 125Hz. The proposed method is validated in wide range of simulated clinical ECG conditions such as arrhythmia (sinus rhythms, supraventricular rhythms, and AV blocks), pulse amplitudes (~100µV to ~3mV), pulse durations (~100µs to ~2ms), pacemaker modes and types (fixed-rate or on-demand single chamber, dual chamber, and bi-ventricular pacing), and physiological noise (tremor). The proposed algorithm demonstrates clinically acceptable detection accuracies with sensitivity and PPV of 98.1 ± 4.4 % and 100 %, respectively. In conclusion, the approach is well suited for integration in long-term wearable ECG sensor devices operating at a low sample frequency to monitor pacemaker function.Clinical Relevance- The proposed system enables real-time long-term continuous assessment of the proper functioning of implanted pacemaker and progression of treatment for cardiac conditions using battery-powered wearable ECG monitors.

With rapid advancement in wearable biosensor technology, systems capable of real time, continuous and ambulatory monitoring of vital signs are increasingly emerging and their use can potentially help improve patient outcome. Monitoring continuous body temperature offers insights into its trend, allows early detection of fever and is critical in several diseases and clinical conditions including septicemia, infectious disease and others. There is a complex interaction between physiological and ambient parameters including heart rate, respiratory rate, muscle rigors and shivers, diaphoresis, local humidity, clothing, body, skin and ambient temperatures among others. This article presents feasibility analysis of a wireless biosensor patch device called as VitalPatch in capturing this physio-ambient-thermodynamic interaction to determine core body temperature, and details comparative performance assessments using oral thermometer and ingestible pill as reference devices. Based on a study on a cohort of 30 subjects with reference oral temperature, the proposed method showed a bias of 0.1 ± 0.37 °C, mean absolute error (MAE) of 0.29 ± 0.25 °C. Another cohort of 22 subjects with continuous core body temperature pill as reference showed a bias of 0.16 ± 0.38 °C and MAE of 0.42 ± 0.22 °C.Clinical Relevance- Non-invasive, continuous and real time body temperature monitoring can lead to earlier fever detection and provides remote patient monitoring that can result in improved patient and clinical outcome.

Validation of biosensor algorithms is paramount for regulated medical devices applied to patient monitoring. We present validation of breathing rate (BR) measurement using a patch medical device via a novel synthetic simulation platform, in-hospital data collection and controlled laboratory study. Single-lead ECG and triaxial body acceleration signals with variability and noise are synthetically generated and quantized for a constellation according to the input parameters of heart rate (HR) as a fundamental frequency $( f_{c})$ of ECG and reference BR as a modulating frequency $( f_{r})$. Synthetic signals are input to the BR algorithms and the performance of output BRs are evaluated for a region-of-interest of the constellation $( f_{c}/ f_{r}\,\ge 3$ & $f_{c}/ f_{r}\,\le 8)$ accounting the Nyquist and physiological varability. The performances of patch sensor's BR are also evaluated in 13 post-operative patients with reference to a clinical bedside monitor and in 57 subjects carrying out a controlled laboratory protocol with reference to capnography. The synthetic simulations revealed mean absolute error (MAE) of 0.8±0.6 brpm and standard deviation of absolute error of 0.3±0.2 brpm for the BR algorithms of patch sensor. The controlled laboratory testing revealed MAE of 1.7±0.7 brpm (n=57) for stationary conditions. The proposed simulation platform can be useful for developmental refinement or validation of BR measurement prior to testing in humans at clinical or laboratory conditions and applicable for testing other patient monitoring devices with modular modifications.

Continuous remote monitoring with convenient wireless sensors is attractive for early detection of patient deterioration, preventing adverse events and leading to better patient care. This article presents an innovative sensor design of VitalPatch, a fully disposable wireless biosensor, for remote continuous monitoring, and details the performance assessments from bench testing and laboratory validation in 57 subjects. The bench testing results reveal that VitalPatch's QRS detection had a positive predictive value of $> 99$% from testing with ECG databases. The accuracies of HR, BR and skin temp (in mean absolute error, MAE) from bench testing were $< 5$ bpm, $< 1$ brpm, $< 1 ^{ \circ}C$ respectively. The laboratory testing in 57 subjects revealed the accuracy of HR and BR to be $2.2 \pm 1.5$ bpm and $1.7 \pm 0.7$ brpm respectively for stationary periods. The absolute percent error in detecting steps was $4.7 \pm 4.6$%, and the accuracy in detecting posture was $96.4 \pm 3.1$%. Meanwhile, the specificity and sensitivity of fall detection $( \mathrm {n}=20)$ was found to be 100% and 93.8%, respectively. In conclusion, VitalPatch biosensor demonstrated clinically acceptable accuracies for its vital signs and actigraphy metrics applicable for continuous unobtrusive patient monitoring.