Wearable feedback systems for rehabilitation

In this paper we describe LiveNet, a flexible wearable platform intended for long-term ambulatory health monitoring with real-time data streaming and context classification. Based on the MIT Wearable Computing Group's distributed mobile system architecture, LiveNet is a stable, accessible system that combines inexpensive, commodity hardware; a flexible sensor/peripheral interconnection bus; and a powerful, light-weight distributed sensing, classification, and inter-process communications software architecture to facilitate the development of distributed real-time multi-modal and context-aware applications. LiveNet is able to continuously monitor a wide range of physiological signals together with the user's activity and context, to develop a personalized, data-rich health profile of a user over time. We demonstrate the power and functionality of this platform by describing a number of health monitoring applications using the LiveNet system in a variety of clinical studies that are underway. Initial evaluations of these pilot experiments demonstrate the potential of using the LiveNet system for real-world applications in rehabilitation medicine

Development of a Signal Processing Library for Extraction of SpO2, HR, HRV, and RR from Photoplethysmographic Waveforms

Non-invasive remote physiological monitoring of soldiers on the battlefield has the potential to provide fast, accurate status assessments that are key to improving the survivability of critical injuries. The development of WPI’s wearable wireless pulse oximeter, designed for field-based applications, has allowed for the optimization of important hardware features such as physical size and power management. However, software-based digital signal processing (DSP) methods are still required to perform physiological assessments. This research evaluated DSP methods that were capable of providing arterial oxygen saturation (SpO2), heart rate (HR), heart rate variability (HRV), and respiration rate (RR) measurements derived from data acquired using a single optical sensor. In vivo experiments were conducted to evaluate the accuracies of the processing methods across ranges of physiological conditions. Of the algorithms assessed, 13 SpO2 methods, 1 HR method, 6 HRV indices, and 4 RR methods were identified that provided clinically acceptable measurement accuracies and could potentially be employed in a wearable pulse oximeter

Hospital Ward Alarm Fatigue Reduction Through Integrated Medical Device and Hospital System Policy Instruction

The objective of this project is to reduce alarm fatigue in American hospital systems and improve patient care. This objective will be addressed by providing a secure online knowledge base of proper settings for medical devices in conjunction with hospital­specific policy about alarm protocol, at the point of care, to instruct clinical staff with accuracy and consistency

Wireless body sensor networks for health-monitoring applications

This is an author-created, un-copyedited version of an article accepted for publication in Physiological Measurement. The publisher is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at http://dx.doi.org/10.1088/0967-3334/29/11/R01

An Energy-Autonomous Smart Shirt employing wearable sensors for Users’ Safety and Protection in Hazardous Workplaces

none4siWearable devices represent a versatile technology in the IoT paradigm, enabling noninvasive and accurate data collection directly from the human body. This paper describes the development of a smart shirt to monitor working conditions in particularly dangerous workplaces. The wearable device integrates a wide set of sensors to locally acquire the user’s vital signs (e.g., heart rate, blood oxygenation, and temperature) and environmental parameters (e.g., the concentration of dangerous gas species and oxygen level). Electrochemical gas-monitoring modules were designed and integrated into the garment for acquiring the concentrations of CO, O2, CH2O, and H2S. The acquired data are wirelessly sent to a cloud platform (IBM Cloud), where they are displayed, processed, and stored. A mobile application was deployed to gather data from the wearable devices and forward them toward the cloud application, enabling the system to operate in areas where aWiFi hotspot is not available. Additionally, the smart shirt comprises a multisource harvesting section to scavenge energy from light, body heat, and limb movements. Indeed, the wearable device integrates several harvesters (thin-film solar panels, thermoelectric generators (TEGs), and piezoelectric transducers), a low-power conditioning section, and a 380 mAh LiPo battery to accumulate the recovered charge. Field tests indicated that the harvesting section could provide up to 216 mW mean power, fully covering the power requirements (P = 1.86 mW) of the sensing, processing, and communication sections in all considered conditions (3.54 mW in the worst-case scenario). However, the 380 mAh LiPo battery guarantees about a 16-day lifetime in the complete absence of energy contributions from the harvesting section.Special Issue “Innovative Materials, Smart Sensors and IoT-based Electronic Solutions for Wearable Applications”, https://www.mdpi.com/journal/applsci/special_issues/Materials_Sensors_Electronic_Solutions_Wearable_ApplicationsopenRoberto De Fazio, Abdel-Razzak Al-Hinnawi, Massimo De Vittorio, Paolo ViscontiDE FAZIO, Roberto; Al-Hinnawi, Abdel-Razzak; DE VITTORIO, Massimo; Visconti, Paol

An at Home Cardiorespiratory Monitor in Low Income Countries

ME450 Capstone Design and Manufacturing Experience: Winter 2021This project starts the design process of a device that helps address the issue of Respiratory Syncytial Virus (RSV) in infants in low income countries. It is a pulse oximeter that is modified to infants small features and constant movement. It also considers the environmental conditions that are associated with most low income countries. The current solution for the problem is a two housing monitor that would be worn the infant's ankle and foot to consistently monitor their blood oxygen levels while they sleep.Prof. Aubree Gordon, Caroline Soyars: Global Health Design Initiativehttp://deepblue.lib.umich.edu/bitstream/2027.42/167653/1/Team_10-Cardiorespiratory_Monitor.pd

Ultra-Low Power Wirel ess Sensor Networks: Overview of Applications , Design Requirements and Challenges

Wireless Sensor Networks (WSNs) have received significant attention from various researchers in terms of its architecture, design, challenges and supporting technologies, and so on. Also, their applications to different aspect such as structural health monitoring, health care, precision agriculture, intelligent transport systems have been reported. Though, some authors have reviewed different aspects of wireless sensor nodes, including applications, this paper presents a short survey of selected literature from a pool of articles reporting application cases of ultra-low power WSNs published in 2010- 2017. In this paper, specific design requirements for using ultra-low power sensor nodes were highlighted. In addition, existing solutions to challenges encountered when using WSNs for the selected applications were examined. This short survey will help readers and practitioners with scholarly resource needed for understanding the state-of-the-art in ultra-low power wireless sensor applications and offers insight into areas for further research. It will also help researchers to become aware of potential collaborators in future works involving WSNs