scholarly journals A Method of Data Aggregation for Wearable Sensor Systems

Sensors ◽  
2016 ◽  
Vol 16 (7) ◽  
pp. 954 ◽  
Author(s):  
Bo Shen ◽  
Jun-Song Fu
Keyword(s):  
Data Aggregation ◽  
Sensor Systems ◽  
Wearable Sensor

Laboratory Validation of Two Wearable Sensor Systems for Measuring Head Impact Severity in Football Players

2015 ◽  
Vol 44 (4) ◽  
pp. 1257-1274 ◽  
Author(s):  
Gunter P. Siegmund ◽  
Kevin M. Guskiewicz ◽  
Stephen W. Marshall ◽  
Alyssa L. DeMarco ◽  
Stephanie J. Bonin
Keyword(s):  
Head Impact ◽  
Football Players ◽  
Sensor Systems ◽  
Wearable Sensor ◽  
Measuring Head

scholarly journals Energy efficient enhanced tree structured compression model (ET-CM) for data aggregation in wireless sensor networks

2018 ◽  
Vol 7 (2.17) ◽  
pp. 1
Author(s):  
Nandoori Srikanth ◽  
M Siva ganga prasad
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Energy Efficient ◽  
Information Measure ◽  
Transmission Time ◽  
Wireless Sensor ◽  
Sensor Systems ◽  
Compression Model ◽  
Remote Sensor

Compression, is a typical strategy to decrease information measure by taking care of information excess, can be utilized as a part of postpone delicate remote sensor systems (WSNs) to diminish end-to-end bundle delay as it can lessen parcel transmission time and conflict on the remote channel. All together for remote sensor systems to misuse flag, flag information must be gathered at a large number of sensors and must be shared among the sensors. Huge sharing of information among the sensors repudiates the prerequisites (vitality effectiveness, low inactivity and high exactness) of remote organized sensor. This paper manages the investigation of compressive proportion and vitality utilization in the system by contrasting and the current compressive strategies.  

Design Methodology for Context-Aware Wearable Sensor Systems

2005 ◽  
pp. 220-236 ◽  
Author(s):  
Urs Anliker ◽  
Holger Junker ◽  
Paul Lukowicz ◽  
Gerhard Tröster
Keyword(s):  
Design Methodology ◽  
Context Aware ◽  
Sensor Systems ◽  
Wearable Sensor

scholarly journals A Review of Wearable Sensor Systems to Monitor Plantar Loading in the Assessment of Diabetic Foot Ulcers

2020 ◽  
pp. 1-1 ◽  
Author(s):  
Lefan Wang ◽  
Dominic Jones ◽  
Graham J. Chapman ◽  
Heidi J. Siddle ◽  
David A. Russell ◽  
...  
Keyword(s):  
Diabetic Foot ◽  
Foot Ulcers ◽  
Sensor Systems ◽  
Diabetic Foot Ulcers ◽  
Wearable Sensor

Wearable sensor systems: The challenges

2011 ◽  
Author(s):  
E. McAdams ◽  
A. Krupaviciute ◽  
C. Gehin ◽  
E. Grenier ◽  
B. Massot ◽  
...  
Keyword(s):  
Sensor Systems ◽  
Wearable Sensor

scholarly journals What Does Big Data Mean for Wearable Sensor Systems?

2014 ◽  
Vol 23 (01) ◽  
pp. 135-142 ◽  
Author(s):  
N. H. Lovell ◽  
G. Z. Yang ◽  
A. Horsch ◽  
P. Lukowicz ◽  
L. Murrugarra ◽  
...  
Keyword(s):  
Big Data ◽  
Health Management ◽  
Wearable Sensors ◽  
Scientific Progress ◽  
Sensor Data ◽  
Sensor Systems ◽  
Wearable Sensor ◽  
Negative Consequences ◽  
Inference Problems ◽  
Care Working Group

Summary Objectives:The aim of this paper is to discuss how recent developments in the field of big data may potentially impact the future use of wearable sensor systems in healthcare. Methods: The article draws on the scientific literature to support the opinions presented by the IMIA Wearable Sensors in Health-care Working Group. Results: The following is discussed: the potential for wearable sensors to generate big data; how complementary technologies, such as a smartphone, will augment the concept of a wearable sensor and alter the nature of the monitoring data created; how standards would enable sharing of data and advance scientific progress. Importantly, attention is drawn to statistical inference problems for which big datasets provide little assistance, or may hinder the identification of a useful solution. Finally, a discussion is presented on risks to privacy and possible negative consequences arising from intensive wearable sensor monitoring. Conclusions: Wearable sensors systems have the potential to generate datasets which are currently beyond our capabilities to easily organize and interpret. In order to successfully utilize wearable sensor data to infer wellbeing, and enable proactive health management, standards and ontologies must be developed which allow for data to be shared between research groups and between commercial systems, promoting the integration of these data into health information systems. However, policy and regulation will be required to ensure that the detailed nature of wearable sensor data is not misused to invade privacies or prejudice against individuals.

scholarly journals Recent Advances on IoT-Assisted Wearable Sensor Systems for Healthcare Monitoring

Biosensors ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 372
Author(s):  
Shwetank Dattatraya Mamdiwar ◽  
Akshith R ◽  
Zainab Shakruwala ◽  
Utkarsh Chadha ◽  
Kathiravan Srinivasan ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Data Processing ◽  
Essential Role ◽  
Communication Technologies ◽  
Wearable Technology ◽  
Healthcare Industry ◽  
Sensor Systems ◽  
Wearable Sensor ◽  
The World ◽  
Healthcare Monitoring

IoT has played an essential role in many industries over the last few decades. Recent advancements in the healthcare industry have made it possible to make healthcare accessible to more people and improve their overall health. The next step in healthcare is to integrate it with IoT-assisted wearable sensor systems seamlessly. This review rigorously discusses the various IoT architectures, different methods of data processing, transfer, and computing paradigms. It compiles various communication technologies and the devices commonly used in IoT-assisted wearable sensor systems and deals with its various applications in healthcare and their advantages to the world. A comparative analysis of all the wearable technology in healthcare is also discussed with tabulation of various research and technology. This review also analyses all the problems commonly faced in IoT-assisted wearable sensor systems and the specific issues that need to be tackled to optimize these systems in healthcare and describes the various future implementations that can be made to the architecture and the technology to improve the healthcare industry.

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