scholarly journals Simulating the impact of noise on gait features extracted from smartphone sensor-data for the remote assessment of movement disorders

2021 ◽  
Author(s):  
Guy Bogaarts ◽  
Mattia Zanon ◽  
Frank Dondelinger ◽  
Adrian Derungs ◽  
Florian Lipsmeier ◽  
...  
Keyword(s):  
Movement Disorders ◽  
Sensor Data ◽  
Gait Features ◽  
Remote Assessment ◽  
The Impact ◽  
Smartphone Sensor

scholarly journals LSTM Networks Using Smartphone Data for Sensor-Based Human Activity Recognition in Smart Homes

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1636
Author(s):  
Sakorn Mekruksavanich ◽  
Anuchit Jitpattanakul
Keyword(s):  
Activity Recognition ◽  
Human Activity ◽  
Recognition Performance ◽  
Human Activity Recognition ◽  
Optimization Techniques ◽  
Bayesian Optimization ◽  
Sensor Data ◽  
Lstm Network ◽  
The Impact ◽  
Smartphone Sensor

Human Activity Recognition (HAR) employing inertial motion data has gained considerable momentum in recent years, both in research and industrial applications. From the abstract perspective, this has been driven by an acceleration in the building of intelligent and smart environments and systems that cover all aspects of human life including healthcare, sports, manufacturing, commerce, etc. Such environments and systems necessitate and subsume activity recognition, aimed at recognizing the actions, characteristics, and goals of one or more individuals from a temporal series of observations streamed from one or more sensors. Due to the reliance of conventional Machine Learning (ML) techniques on handcrafted features in the extraction process, current research suggests that deep-learning approaches are more applicable to automated feature extraction from raw sensor data. In this work, the generic HAR framework for smartphone sensor data is proposed, based on Long Short-Term Memory (LSTM) networks for time-series domains. Four baseline LSTM networks are comparatively studied to analyze the impact of using different kinds of smartphone sensor data. In addition, a hybrid LSTM network called 4-layer CNN-LSTM is proposed to improve recognition performance. The HAR method is evaluated on a public smartphone-based dataset of UCI-HAR through various combinations of sample generation processes (OW and NOW) and validation protocols (10-fold and LOSO cross validation). Moreover, Bayesian optimization techniques are used in this study since they are advantageous for tuning the hyperparameters of each LSTM network. The experimental results indicate that the proposed 4-layer CNN-LSTM network performs well in activity recognition, enhancing the average accuracy by up to 2.24% compared to prior state-of-the-art approaches.

THE IMPACT OF ATTENTIONAL FOCUS ON THE TREATMENT OF MUSCULOSKELETAL AND MOVEMENT DISORDERS

2017 ◽  
Vol 12 (6) ◽  
pp. 901-907 ◽  
Author(s):  
Christopher Hunt ◽  
Arsenio Paez ◽  
Eric Folmar
Keyword(s):  
Movement Disorders ◽  
Attentional Focus ◽  
The Impact

scholarly journals WON-OCDMA System Based on MW-ZCC Codes for Applications in Optical Wireless Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 539
Author(s):  
Saleh Seyedzadeh ◽  
Andrew Agapiou ◽  
Majid Moghaddasi ◽  
Milan Dado ◽  
Ivan Glesk
Keyword(s):  
Optical Networks ◽  
Video Surveillance ◽  
Multiple Access ◽  
Optical Sensing ◽  
Multiple Access Interference ◽  
Service Differentiation ◽  
Sensor Data ◽  
Variable Weight ◽  
Code Division Multiple ◽  
The Impact

The growing demand for extensive and reliable structural health monitoring resulted in the development of advanced optical sensing systems (OSS) that in conjunction with wireless optical networks (WON) are capable of extending the reach of optical sensing to places where fibre provision is not feasible. To support this effort, the paper proposes a new type of a variable weight code called multiweight zero cross-correlation (MW-ZCC) code for its application in wireless optical networks based optical code division multiple access (WON-OCDMA). The code provides improved quality of service (QoS) and better support for simultaneous transmission of video surveillance, comms and sensor data by reducing the impact of multiple access interference (MAI). The MW-ZCC code’s power of two code-weight properties provide enhanced support for the needed service differentiation provisioning. The performance of this novel code has been studied by simulations. This investigation revealed that for a minimum allowable bit error rate of 10−3, 10−9 and 10−12 when supporting triple-play services (sensing, datacomms and video surveillance, respectively), the proposed WON-OCDMA using MW-ZCC codes could support up to 32 simultaneous services over transmission distances up to 32 km in the presence of moderate atmospheric turbulence.

scholarly journals Successful Transitions to Remote Assessments and Technology Installations due to COVID-19: The I-CONECT Project

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 958-958
Author(s):  
Khoa Nguyen ◽  
Mattie McDonald ◽  
Colton Scavone ◽  
Nora Mattek ◽  
Jeffrey Kaye ◽  
...  
Keyword(s):  
Social Interaction ◽  
Community Dwelling ◽  
Controlled Clinical Trial ◽  
Cognitive Assessments ◽  
Video Chat ◽  
Remote Assessment ◽  
Study Population ◽  
Support Team ◽  
Socially Isolated ◽  
The Impact

Abstract I-CONECT is a randomized controlled clinical trial to examine the impact of social interaction delivered via video-chat on cognitive function (clinicaltrials.gov number: NCT02871921, project website: www.I-CONECT.org ). We aimed to enroll 320 community-dwelling socially isolated older adults (age >=75 years). The recruitment of participants has started in 2018 and was ongoing when COVID-19 pandemic began. Video chat and telephone-based social interaction interventions did not change during COVID-19. However, new recruitment and cognitive assessments, which require in-person contact and deployment and retrieval of video chat devices in participant homes, were suspended due to the nature of our study population (i.e., older age, higher likelihood of comorbidities). Recently we were able to successfully switch to complete remote assessments including 1) telephone-based cognitive assessments using T-COG (Telephone Cognitive Assessment battery), and 2) contactless delivery of our study devices (Chrome books and electronic pill boxes) for subject self-installation. Our creative approach to self-installations includes color coded pictures and an easy-to-follow installation manual, accompanied by remote instruction and support via telephone. This poster introduces our remote assessment and installation protocol and participant and technical support team feedback regarding this new contactless protocol. This presentation provides useful guidance for future studies considering completely remote assessment and telemedicine approaches.

scholarly journals Ambient Air Quality Measurement with Low-Cost Optical and Electrochemical Sensors: An Evaluation of Continuous Year-Long Operation

Environments ◽  
2021 ◽  
Vol 8 (11) ◽  
pp. 114
Author(s):  
Jiří Bílek ◽  
Ondřej Bílek ◽  
Petr Maršolek ◽  
Pavel Buček
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Sensor Network ◽  
Electrochemical Sensors ◽  
Reference Method ◽  
Ambient Air ◽  
Sensor Data ◽  
Dust Particles ◽  
Concentration Changes ◽  
The Impact

Sensor technology is attractive to the public due to its availability and ease of use. However, its usage raises numerous questions. The general trustworthiness of sensor data is widely discussed, especially with regard to accuracy, precision, and long-term signal stability. The VSB-Technical University of Ostrava has operated an air quality sensor network for more than two years, and its large sets of valid results can help in understanding the limitations of sensory measurement. Monitoring is focused on the concentrations of dust particles, NO2, and ozone to verify the impact of newly planted greenery on the reduction in air pollution. The sensor network currently covers an open field on the outskirts of Ostrava, between Liberty Ironworks and the nearby ISKO1650 monitoring station, where some of the worst air pollution levels in the Czech Republic are regularly measured. In the future, trees should be allowed to grow over the sensors, enabling assessment of the green barrier effect on air pollution. As expected, the service life of the sensors varies from 1 to 3 years; therefore, checks are necessary both prior to the measurement and regularly during operation, verifying output stability and overall performance. Results of the PMx sensory measurements correlated well with the reference method. Concentration values measured by NO2 sensors correlated poorly with the reference method, although timeline plots of concentration changes were in accordance. We suggest that a comparison of timelines should be used for air quality evaluations, rather than particular values. The results showed that the sensor measurements are not yet suitable to replace the reference methods, and dense sensor networks proved useful and robust tools for indicative air quality measurements (AQM).

Internet of Things in E-Health

2017 ◽  
pp. 191-197 ◽  
Author(s):  
Branka Rodić Trmčić ◽  
Aleksandra Labus ◽  
Svetlana Mitrović ◽  
Vesna Buha ◽  
Gordana Stanojević
Keyword(s):  
Internet Of Things ◽  
Health Behavior ◽  
Well Being ◽  
Sensor Data ◽  
Main Task ◽  
Preventive Actions ◽  
Framework Model ◽  
The Impact ◽  
Health And Well Being ◽  
Improve Health

The main task of Internet of Things in eHealth solutions is to collect data, connect people, things and processes. This provides a wealth of information that can be useful in decision-making, improving health and well-being. The aim of this study is to identify framework of sensors and application health services to detect sources of stress and stressors and make them visible to users. Also, we aim at extracting relationship between event and sensor data in order to improve health behavior. Evaluation of the proposed framework model will be performed. Model is based on Internet of Things in eHealth and is going to aim to improve health behavior. Following the established pattern of behavior realized through wearable system users will be proposed a preventive actions model. Further, it will examine the impact of changing health behavior on habits, condition and attitudes in relation to well-being and prevention.

scholarly journals Optical Wireless Network Design for Off-Body-Sensor Based Monitoring

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
T. B. Hoang ◽  
S. Sahuguede ◽  
A. Julien-Vergonjanne
Keyword(s):  
Health Monitoring ◽  
Visible Light Communication ◽  
The Body ◽  
Sensor Data ◽  
Body Parts ◽  
Optical Technology ◽  
Wireless Network Design ◽  
Response Sets ◽  
Trade Offs ◽  
The Impact

In this article, we propose an all-optical bidirectional wireless communication system for off-body sensor communication. Optical technology uses infrared (IR) for uplinks and visible light communication (VLC) for downlinks. From numerical simulations, we discuss the impact of body sensor positions on IR and VLC channels. Our goal is to evaluate the possibilities of using optical technology to transmit sensor data for extreme positions such as the ankle, for which the presence of the body creates blockages. In addition, we also consider the variations in orientation of transceivers due to random mobility of body parts during normal movement. Based on a statistical approach, we evaluate performance in terms of outage probability using channel impulse response sets corresponding to the studied scenario, which is health monitoring. Considering a given quality of service, we address trade-offs related to emitting power and data rate. We discuss the results regarding sensor node position and body reflectivity specifically for ankle sensors, corresponding to an extreme but realistic position in the health-monitoring context.

Sign in / Sign up

Export Citation Format

Share Document