Validation Studies

Full Publications list featuring Biostrap/Wavelet devices

Sep 10, 2018

Design Rationale and Performance Evaluation of the Wavelet Health Wristband: Benchtop Validation of a Wrist-Worn Physiological Signal Recorder

This study aimed to evaluate the accuracy of the biometric estimates and signal quality of the wristband.

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Jun 9, 2018

Preliminary Evaluation of a Wrist Wearable Heart Rate Sensor for the Detection of Undiagnosed Atrial Fibrillation in a Real-World Setting

A wearable, non-ECG sensor will allow for rhythm monitoring for longer periods of time and therefore potentially provide the evidence to motivate future large studies on photoplethysmography (PPG) based AF detection.

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Mar 4, 2018

Estimation of HRV and SpO2 from wrist-worn commercial sensors for clinical settings

We describe an evaluation of photoplethysmography (PPG) signals with two wavelengths channels (infrared and red) using a wrist-worn sensor for the estimation of heart rate variability (HRV) and oxygen saturation (SpO2)

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Nov 13, 2017

Machine Learning Detection of Obstructive Hypertrophic Cardiomyopathy Using a Wearable Biosensor

Arterial pulsewaves recorded with a wearable biosensor and analyzed with machine learning algorithms could identify a signature of oHCM when compared to unaffected controls.

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Nov 13, 2017

Preliminary Evaluation of a Wrist Wearable Heart Rate Sensor for the Detection of Undiagnosed Atrial Fibrillation in a Real-World Setting

A wearable, non-ECG sensor will allow for rhythm monitoring for longer periods of time and therefore potentially provide the evidence to motivate future large studies on photoplethysmography (PPG) based AF detection.

View study
Nov 13, 2017

Utility of A Wristband Device as a Portable Screening Tool for Obstructive Sleep Apnea

This study is designed to assess (1) the accuracy of nocturnal biometric measurements collected by an investigational wrist-worn device, and (2) its utility as a portable screening device for detection of apnea.

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Jun 20, 2017

Assessment of pulse wave pressure changes for detection of arrhythmia and comorbidities using a wrist-worn wearable device

This study aims to evaluate the utility of a wrist-worn device for detection of AF episodes as well as to study pulse wave changes and patient activity.

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Rationale and design of a home-based trial using wearable sensors to detect asymptomatic atrial fibrillation in a targeted population: The mHealth Screening To Prevent Strokes (mSToPS) trial.

The trial's primary objective is to determine, in a real-world setting, whether using wearable sensors in a risk-targeted screening population can diagnose asymptomatic AF more effectively than routine care. Additional key objectives include (1) exploring 2 rhythm-monitoring strategies-electrocardiogram-based and exploratory pulse wave-based-for detection of new AF, and (2) comparing long-term clinical and resource outcomes among groups.

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Bluetooth devices for the optimization of patients' workflow in a radiation oncology department.

We propose to extend the application of this widespread technology even in the medical environment. The aim of our work is to apply BT-ACTs for workflow management and patients’ performance monitoring in a Radiation Oncology Department. Indeed, in such medical department working on outpatients based regimen, workflow and clinical control may be complex

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Changes in physiologic signals during sleep due to arrhythmia

We conducted a respective study of our data and sought to evaluate the value of this technology in identifying atrial fibrillation (AF), resulting in changes to clinical management of the patient.

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Cardiorespiratory Physiology Remotely Monitored via Wearable Wristband Photoplethysmography: Feasibility and Initial Benchmarking

Feasibility and benchmarking in the clinical environment is a necessary first step before testing the prospective value of these remote monitored wearable-derived physiology measurements.

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Trial design of the WATCH AF trial - SmartWATCHes for detection of atrial fibrillation

In the WATCH AF study, this algorithm is tested for the first time with PPG signals from a smartwatch (Samsung) and a wristband (Wavelet health). Our study aims to determine the accuracy of these applications compared to an ambulatory ECG system.

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