Development of a body sensor network to detect motor patterns of epileptic seizures.

The objective of this study was the development of a remote monitoring system to monitor and detect simple motor seizures. Using accelerometer-based kinematic sensors, data were gathered from subjects undergoing medication titration at the Beth Israel Deaconess Medical Center. Over the course of the study, subjects repeatedly performed a predefined set of instrumental activities of daily living (iADLs).

Longitudinal monitoring of patients with Parkinson's disease via wearable sensor technology in the home setting.

Objective longitudinal monitoring of symptoms related motor fluctuations can provide valuable information for the clinical management of patients with Parkinson's disease. Current methods for long-term monitoring of motor fluctuations, such as patient diaries, are ineffective due to their time consuming and subjective nature. Researchers have shown that wearable sensors such as accelerometers can be used to gather objective information about a patient's motor symptoms.

Home monitoring of patients with Parkinson's disease via wearable technology and a web-based application.

Objective long-term health monitoring can improve the clinical management of several medical conditions ranging from cardiopulmonary diseases to motor disorders. In this paper, we present our work toward the development of a home-monitoring system. The system is currently used to monitor patients with Parkinson's disease who experience severe motor fluctuations.

A web-based system for home monitoring of patients with Parkinson's disease using wearable sensors.

This letter introduces MercuryLive, a platform to enable home monitoring of patients with Parkinson's disease (PD) using wearable sensors. MercuryLive contains three tiers: a resource-aware data collection engine that relies upon wearable sensors, web services for live streaming and storage of sensor data, and a web-based graphical user interface client with video conferencing capability. Besides, the platform has the capability of analyzing sensor (i.

Monitoring motor fluctuations in patients with Parkinson's disease using wearable sensors.

This paper presents the results of a pilot study to assess the feasibility of using accelerometer data to estimate the severity of symptoms and motor complications in patients with Parkinson's disease. A support vector machine (SVM) classifier was implemented to estimate the severity of tremor, bradykinesia and dyskinesia from accelerometer data features. SVM-based estimates were compared with clinical scores derived via visual inspection of video recordings taken while patients performed a series of standardized motor tasks.

Creating a hospital-wide patient safety net: Design and deployment of ZigBee vital sign sensors.

Advancements in wireless technologies can enable patient monitors to be far more versatile than ones that are used today. We developed wireless vital sign sensors that operate on a robust, infrastructure-independent, and instantaneously deployable wireless communication network. These sensors were easily and rapidly deployed in a diverse variety of care settings to provide continuous patient monitoring.

Analysis of feature space for monitoring persons with Parkinson's disease with application to a wireless wearable sensor system.

We present work to develop a wireless wearable sensor system for monitoring patients with Parkinson's disease (PD) in their homes. For monitoring outside the laboratory, a wearable system must not only record data, but also efficiently process data on-board. This manuscript details the analysis of data collected using tethered wearable sensors.

Vital signs monitoring and patient tracking over a wireless network.

Patients at a disaster scene can greatly benefit from technologies that continuously monitor their vital status and track their locations until they are admitted to the hospital. We have designed and developed a real-time patient monitoring system that integrates vital signs sensors, location sensors, ad-hoc networking, electronic patient records, and web portal technology to allow remote monitoring of patient status. This system shall facilitate communication between providers at the disaster scene, medical professionals at local hospitals, and specialists available for consultation from distant facilities.

A portable, low-power, wireless two-lead EKG system.

Sensor devices ("motes") which integrate an embedded microprocessor, low-power radio and a limited amount of storage have the potential to significantly enhance the provision of emergency medical care. Wearable vital sign sensors can wirelessly monitor patient condition, alerting healthcare providers to changes in status while simultaneously delivering data to a backend archival system for longer-term storage. As part of the CodeBlue initiative at Harvard University, we previously developed a mote-based pulse oximetry module which gathers data from a noninvasive finger sensor and transmits it wirelessly to a base station.

The design of a decentralized electronic triage system.

The Advanced Health and Disaster Aid Network (AID-N) project seeks to identify unmet needs of emergency response teams in the Washington, DC area during mass casualty incidents and conduct feasibility tests of technology-based solutions. The decentralized electronic triage and sensing system uses low power, electronic triage sensors to monitor the vital signs of patients and provide location tracking capabilities. The robust, decentralized location tracking software runs on a small, embedded system with limited memory and computational power that efficiently locates patients.