Using Wearable Sensors for Real-Time Recognition Tasks in Games of Martial Arts - An Initial Experiment

2006 ◽  
Author(s):  
Ernst A. Heinz ◽  
Kai S. Kunze ◽  
Matthias Gruber ◽  
David Bannach ◽  
Paul Lukowicz
Keyword(s):  
Real Time ◽  
Martial Arts ◽  
Wearable Sensors ◽  
Initial Experiment

scholarly journals A Real-Time, Automatic, and Dynamic Scheduling and Control System for PET Patients Based on Wearable Sensors

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1104
Author(s):  
Shin-Yan Chiou ◽  
Kun-Ju Lin ◽  
Ya-Xin Dong
Keyword(s):  
Control System ◽  
Real Time ◽  
Human Error ◽  
Dynamic Scheduling ◽  
Wearable Sensors ◽  
Time Data ◽  
Scan Time ◽  
Number Of Patients ◽  
And Control ◽  
Automatic Scheduling

Positron emission tomography (PET) is one of the commonly used scanning techniques. Medical staff manually calculate the estimated scan time for each PET device. However, the number of PET scanning devices is small, the number of patients is large, and there are many changes including rescanning requirements, which makes it very error-prone, puts pressure on staff, and causes trouble for patients and their families. Although previous studies proposed algorithms for specific inspections, there is currently no research on improving the PET process. This paper proposes a real-time automatic scheduling and control system for PET patients with wearable sensors. The system can automatically schedule, estimate and instantly update the time of various tasks, and automatically allocate beds and announce schedule information in real time. We implemented this system, collected time data of 200 actual patients, and put these data into the implementation program for simulation and comparison. The average time difference between manual and automatic scheduling was 7.32 min, and it could reduce the average examination time of 82% of patients by 6.14 ± 4.61 min. This convinces us the system is correct and can improve time efficiency, while avoiding human error and staff pressure, and avoiding trouble for patients and their families.

Joy in the Workplace: A Scoping Review of Positive Emotion and Electroencephalogram

2020 ◽  
Vol 64 (1) ◽  
pp. 1493-1497
Author(s):  
Yaqoub Yusuf ◽  
Jodi Boutte’ ◽  
Asante’ Lloyd ◽  
Emma Fortune ◽  
Renaldo C. Blocker
Keyword(s):  
Real Time ◽  
Scoping Review ◽  
Positive Emotion ◽  
Positive Emotions ◽  
Wearable Sensors ◽  
Recent Advances ◽  
Electrode Systems ◽  
Electroencephalogram Eeg ◽  
Occupational Settings

A workplace that is a conduit for positive emotions can be important to employees retention and can contribute optimal levels of productivity. Validated tools for examining emotions are primarily subjective and retrospective in nature. Recent advances in technology have led to more novel and passive ways of measuring emotions. Wearable sensors, such as electroencephalogram (EEG), are being explored to assess cognitive and physical burdens objectively and in real-time. Therefore, there exists a need to investigate and validate the use of EEG to examine emotions objectively and in real-time. In this paper, we conducted a scoping review of EEG to measure positive emotions and/or indicators of joy in the workplace. Our review results in 22 articles that employ EEG to study joy in occupational settings. Three major themes identified in the analysis include (1) EEG for symptoms detection and outcomes, (2) Populations studied using EEG, and (3) EEG electrode systems.

scholarly journals Wearable Sensor-Based Real-Time Gait Detection: A Systematic Review

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2727
Author(s):  
Hari Prasanth ◽  
Miroslav Caban ◽  
Urs Keller ◽  
Grégoire Courtine ◽  
Auke Ijspeert ◽  
...  
Keyword(s):  
Systematic Review ◽  
Gait Analysis ◽  
Real Time ◽  
Wearable Sensors ◽  
Pressure Sensors ◽  
Clinical Applications ◽  
Performance Comparison ◽  
Heel Strike ◽  
Rule Based ◽  
Pathological Gait

Gait analysis has traditionally been carried out in a laboratory environment using expensive equipment, but, recently, reliable, affordable, and wearable sensors have enabled integration into clinical applications as well as use during activities of daily living. Real-time gait analysis is key to the development of gait rehabilitation techniques and assistive devices such as neuroprostheses. This article presents a systematic review of wearable sensors and techniques used in real-time gait analysis, and their application to pathological gait. From four major scientific databases, we identified 1262 articles of which 113 were analyzed in full-text. We found that heel strike and toe off are the most sought-after gait events. Inertial measurement units (IMU) are the most widely used wearable sensors and the shank and foot are the preferred placements. Insole pressure sensors are the most common sensors for ground-truth validation for IMU-based gait detection. Rule-based techniques relying on threshold or peak detection are the most widely used gait detection method. The heterogeneity of evaluation criteria prevented quantitative performance comparison of all methods. Although most studies predicted that the proposed methods would work on pathological gait, less than one third were validated on such data. Clinical applications of gait detection algorithms were considered, and we recommend a combination of IMU and rule-based methods as an optimal solution.

Wearable sensors bring new benefits to continuous medical monitoring, real time physical activity assessment, baby monitoring and industrial applications

Sensor Review ◽  
2015 ◽  
Vol 35 (2) ◽  
pp. 141-145 ◽  
Author(s):  
Richard Bloss
Keyword(s):  
Real Time ◽  
Continuous Monitoring ◽  
Medical Condition ◽  
Wearable Sensors ◽  
Medical Personnel ◽  
Industrial Applications ◽  
Medical Monitoring ◽  
Content Type ◽  
Doctor's Office ◽  
Monitoring Technologies

Purpose – The purpose of this paper is to review the recent advancements in the development of wearable sensors which can continuously monitor critical medical, assess athletic activity, watch babies and serve industrial applications. Design/methodology/approach – The paper presents an in-depth review of a number of developments in wearable sensing and monitoring technologies for medical, athletic and industrial applications. Researchers and companies around the world were contacted to discuss their direction and progress in this field of medical condition and industrial monitoring, as well as discussions with medical personnel on the perceived benefits of such technology. Findings – Dramatic progress is being made in continuous monitoring of many important body functions that indicate critical medical conditions that can be life-threatening, contribute to blindness or access activity. In the industrial arena, wearable devices bring remote monitoring to a new level. Practical implications – Doctors will be able to replace one-off tests with continuous monitoring that provides a much better continuous real-time “view” into the patient’s conditions. Wearable monitors will help provide much better medical care in the future. Industrial managers and others will be able to monitor and supervise remotely. Originality/value – An expert insight into advancements in medical condition monitoring that replaces the one-time “finger prick” type testing only performed in the doctor’s office. It is also a look at how wearable monitoring is greatly improved and serving athletics, the industry and parents.

Wital: WiFi-based Real-time Vital Signs Monitoring During Sleep

2021 ◽  
Author(s):  
Yu Gu ◽  
Xiang Zhang ◽  
Huan Yan ◽  
Zhi Liu ◽  
Fuji Ren
Keyword(s):  
Real Time ◽  
Wearable Sensors ◽  
Vital Signs ◽  
Implementation Process ◽  
Sleep Monitoring ◽  
Daily Lives ◽  
Vital Signs Monitoring ◽  
Quality Sleep ◽  
Enhancement Method ◽  
Positioning Algorithm

High-quality sleep is essential to our daily lives, and real-time monitoring of vital signs during sleep is beneficial. Current sleep monitoring solutions are mostly based on wearable sensors or cameras, the former is worse for sleep quality, the latter is worse for privacy, dissimilar to such methods, we implement our sleep monitoring system based on COTS WiFi devices. There are two challenges need to be overcome in the system implementation process: First, the torso deformation caused by breathing/heartbeat is weak, how to effectively capture this deformation? Second, movements such as turning over will affect the accuracy of vital signs monitoring, how to quickly distinguish such movements? For the former, we propose a motion detection capability enhancement method based on Rice-K theory and Fresnel theory. For the latter, we propose a sleep motion positioning algorithm based on regularity detection. The experimental results indicated the performance of our method.

Smart Textiles with Biosensing Capabilities

2012 ◽  
Vol 80 ◽  
pp. 129-135 ◽  
Author(s):  
Stéphanie Pasche ◽  
Bastien Schyrr ◽  
Bernard Wenger ◽  
Emmanuel Scolan ◽  
Réal Ischer ◽  
...  
Keyword(s):  
Real Time ◽  
Optical Fibers ◽  
Close Contact ◽  
Biological Fluids ◽  
Wearable Sensors ◽  
Surrounding Medium ◽  
Sol Gel ◽  
The Body ◽  
In Situ Monitoring ◽  
Easy Integration

Real-time, on-body measurement using minimally invasive biosensors opens up new perspectives for diagnosis and disease monitoring. Wearable sensors are placed in close contact with the body, performing analyses in accessible biological fluids (wound exudates, sweat). In this context, a network of biosensing optical fibers woven in textile enables the fabric to measure biological parameters in the surrounding medium. Optical fibers are attractive in view of their flexibility and easy integration for on-body monitoring. Biosensing fibers are obtained by modifying standard optical fibers with a sensitive layer specific to biomarkers. Detection is based on light absorption of the sensing fiber, placing a light source and a detector at both extremities of the fiber. Biosensing optical fibers have been developed for the in situ monitoring of wound healing, measuring pH and the activity of proteases in exudates. Other developments aim at the design of sensing patches based on functionalized, porous sol-gel layers, which can be deposited onto textiles and show optical changes in response to biomarkers. Biosensing textiles present interesting perspectives for innovative healthcare monitoring. Wearable sensors will provide access to new information from the body in real time, to support diagnosis and therapy.

scholarly journals Experimental Validation of Real-Time Ski Jumping Tracking System Based on Wearable Sensors

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7780
Author(s):  
Johannes Link ◽  
Sébastien Guillaume ◽  
Bjoern M. Eskofier
Keyword(s):  
Real Time ◽  
Tracking System ◽  
Wearable Sensors ◽  
Absolute Error ◽  
Opening Angle ◽  
National Team ◽  
Ski Jumping ◽  
Accuracy And Precision ◽  
Real Time Tracking ◽  
Flight Parameters

For sports scientists and coaches, its crucial to have reliable tracking systems to improve athletes. Therefore, this study aimed to examine the validity of a wearable real-time tracking system (WRRTS) for the quantification of ski jumping. The tracking system consists of wearable trackers attached to the ski bindings of the athletes and fixed antennas next to the jumping hill. To determine the accuracy and precision of the WRRTS, four athletes of the German A or B National Team performed 35 measured ski jumps. The WRRTS was used to measure the 3D positions and ski angles during the jump. The measurements are compared with camera measurements for the in-flight parameters and the official video distance for the jumping distance to assess their accuracy. We statistically evaluated the different methods using Bland–Altman plots. We thereby find a mean absolute error of 0.46 m for the jumping distance, 0.12 m for the in-flight positions, and 0.8°, and 3.4° for the camera projected pitch and V-style opening angle, respectively. We show the validity of the presented WRRTS to measure the investigated parameters. Thus, the system can be used as a tracking system during training and competitions for coaches and sports scientists. The real-time feature of the tracking system enables usage during live TV broadcasting.

Implementation of IoT in Healthcare

2020 ◽  
pp. 190-212
Author(s):  
Rashima Mahajan ◽  
Pragya Gupta
Keyword(s):  
Real Time ◽  
High Performance ◽  
Data Transfer ◽  
Wearable Sensors ◽  
Healthcare Sector ◽  
Signal Acquisition ◽  
Useful Life ◽  
Internet Of Healthcare Things ◽  
User Friendly ◽  
Healthcare Architecture

The progressive research in the field of internet of things provides a platform to develop high performance and robust automated systems to control external devices via internet data transfer and cloud computing. The present emerging IoT research including user-friendly and easily-wearable sensors and signal acquisition techniques have made it possible to expand the IoT application areas towards healthcare sector. This chapter aims at providing a rationale behind development of IoT applications in healthcare, architecture details of internet of healthcare things (IoHT), and highlights a step-by-step development of IoT-based heart rate measurement and monitoring system using Arduino. The developed module has been advanced to transmit data over the internet on the ThingSpeak channel to allow remote monitoring in real time. This may help to improve/restore useful life among cardiac patients via real-time monitoring through remote locations.

Remote Patient Monitoring for Healthcare

2019 ◽  
pp. 163-179 ◽  
Author(s):  
Andrew Stranieri ◽  
Venki Balasubramanian
Keyword(s):  
Real Time ◽  
Data Analytics ◽  
Patient Monitoring ◽  
Wearable Sensors ◽  
Data Sets ◽  
Remote Patient Monitoring ◽  
Data Mining Algorithms ◽  
Real Time Analysis ◽  
Huge Data ◽  
Remote Patient

Remote patient monitoring involves the collection of data from wearable sensors that typically requires analysis in real time. The real-time analysis of data streaming continuously to a server challenges data mining algorithms that have mostly been developed for static data residing in central repositories. Remote patient monitoring also generates huge data sets that present storage and management problems. Although virtual records of every health event throughout an individual's lifespan known as the electronic health record are rapidly emerging, few electronic records accommodate data from continuous remote patient monitoring. These factors combine to make data analytics with continuous patient data very challenging. In this chapter, benefits for data analytics inherent in the use of standards for clinical concepts for remote patient monitoring is presented. The openEHR standard that describes the way in which concepts are used in clinical practice is well suited to be adopted as the standard required to record meta-data about remote monitoring. The claim is advanced that this is likely to facilitate meaningful real time analyses with big remote patient monitoring data. The point is made by drawing on a case study involving the transmission of patient vital sign data collected from wearable sensors in an Indian hospital.

Sign in / Sign up

Export Citation Format

Share Document