Cost Analysis of Remote Cardiac Rehabilitation Compared With Facility-Based Cardiac Rehabilitation for Coronary Artery Disease.

Remote cardiac rehabilitation (RCR) represents a promising, noninferior alternative to facility-based cardiac rehabilitation (FBCR). The comparable cost of RCR in US populations has yet to be extensively studied. The purpose of this prospective, patient-selected study of traditional FBCR versus a third-party asynchronous RCR platform was to assess whether RCR can be administered at a comparable cost and clinical efficacy to FBCR.

Effects of a patient-centered digital health intervention in patients referred to cardiac rehabilitation: the Smart HEART clinical trial.

Background: Cardiac rehabilitation (CR) improves outcomes in heart disease yet remains vastly underutilized. Remote CR enhanced with a digital health intervention (DHI) may offer higher access and improved patient-centered outcomes over non-technology approaches. We sought to pragmatically determine whether offering a DHI improves CR access, cardiac risk profile, and patient-reported outcome measures.

Retrospective Analysis and Forecasted Economic Impact of a Virtual Cardiac Rehabilitation Program in a Third-Party Payer Environment.

Participation in cardiac rehabilitation (CR) is recommended for all patients with coronary artery disease (CAD) following hospitalization for acute coronary syndrome or stenting. Yet, few patients participate due to the inconvenience and high cost of attending a facility-based program, factors which have been magnified during the ongoing COVID pandemic. Based on a retrospective analysis of CR utilization and cost in a third-party payer environment, we forecasted the potential clinical and economic benefits of delivering a home-based, virtual CR program, with the goal of guiding future implementation efforts to expand CR access.

Quantifying Human Movement Using the Movn Smartphone App: Validation and Field Study.

Background: The use of embedded smartphone sensors offers opportunities to measure physical activity (PA) and human movement. Big data-which includes billions of digital traces-offers scientists a new lens to examine PA in fine-grained detail and allows us to track people's geocoded movement patterns to determine their interaction with the environment.

Objective: The objective of this study was to examine the validity of the Movn smartphone app (Moving Analytics) for collecting PA and human movement data.

A study of position independent algorithms for phone-based gait frequency detection.

Estimating gait frequency is an important component in the detection and diagnosis of various medical conditions. Smartphone-based kinematic sensors offer a window of opportunity in free-living gait frequency estimation. The main issue with smartphone-based gait frequency estimation algorithms is how to adjust for variations in orientation and location of the phone on the human body.

Hierarchical approaches to estimate energy expenditure using phone-based accelerometers.

Physical inactivity is linked with increase in risk of cancer, heart disease, stroke, and diabetes. Walking is an easily available activity to reduce sedentary time. Objective methods to accurately assess energy expenditure from walking that is normalized to an individual would allow tailored interventions.

Hierarchical Linear Models for Energy Prediction using Inertial Sensors: A Comparative Study for Treadmill Walking.

Walking is a commonly available activity to maintain a healthy lifestyle. Accurately tracking and measuring calories expended during walking can improve user feedback and intervention measures. Inertial sensors are a promising measurement tool to achieve this purpose.

An inertial sensor-based system to develop motor capacity in children with cerebral palsy.

Learning to communicate with alternative augmentative communication devices can be difficult because of the difficulty of achieving controlled interaction while simultaneously learning to communicate. What is needed is a device that harnesses a child's natural motor capabilities and provides the means to reinforce them. We present a kinematic sensor-based system that learns a child's natural gestural capability and allows him/her to practice those capabilities in the context of a game.

Determining energy expenditure from treadmill walking using hip-worn inertial sensors: an experimental study.

We describe an experimental study to estimate energy expenditure during treadmill walking using a single hip-mounted inertial sensor (triaxial accelerometer and triaxial gyroscope). Typical physical-activity characterization using commercial monitors use proprietary counts that do not have a physically interpretable meaning. This paper emphasizes the role of probabilistic techniques in conjunction with inertial data modeling to accurately predict energy expenditure for steady-state treadmill walking.

Energy estimation of treadmill walking using on-body accelerometers and gyroscopes.

Walking is the most common activity among people who are physically active. Standard practice physical activity characterization from body-mounted inertial sensors uses accelerometer-generated counts. There are two problems with this - imprecison (due to usage of proprietary counts) and incompleteness (due to incomplete description of motion).