2014 11th International Conference on Wearable and Implantable Body Sensor Networks Workshops最新文献

Applications of the PowerGlove for Measurement of Finger Kinematics power love在手指运动测量中的应用

2014 11th International Conference on Wearable and Implantable Body Sensor Networks Workshops Pub Date : 2014-06-16 DOI: 10.1109/BSN.WORKSHOPS.2014.19

J. C. van den Noort, Kees J van Dijk, H. Kortier, N. van Beek, R. Verhagen, L. Bour, P. Veltink

{"title":"Applications of the PowerGlove for Measurement of Finger Kinematics","authors":"J. C. van den Noort, Kees J van Dijk, H. Kortier, N. van Beek, R. Verhagen, L. Bour, P. Veltink","doi":"10.1109/BSN.WORKSHOPS.2014.19","DOIUrl":"https://doi.org/10.1109/BSN.WORKSHOPS.2014.19","url":null,"abstract":"Hand motor control is quite complex and measurement of hand kinematics is therefore of high interest in many fields. A new measurement system based on miniature inertial and magnetic sensors, the PowerGlove, has been developed. In the near future, the PowerGlove will be applied to study finger interdependency in healthy elderly and to objectively quantify hand motor symptoms in Parkinson's disease. To validate and test the feasibility of the PowerGlove for future application Validation experiments with an optoelectronic marker system and pilot experiments in young healthy subjects were performed, specifically focused on measurement of metacarpophalangeal joint flexion/extension (MCP), proximal interphalangeal joint flexion (PIP) and finger tapping. Mean root mean square (RMS) difference between the optoelectronic marker system and the PowerGlove was less than 5 degrees. The results from the pilot experiments showed the feasibility of the PowerGlove to quantify each finger and joint movement in different movement tasks that are of interest for application in aged subjects and Parkinson disease patients.","PeriodicalId":311910,"journal":{"name":"2014 11th International Conference on Wearable and Implantable Body Sensor Networks Workshops","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131612636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

A Flexible Wearable Sensor Network for Bio-Signals and Human Activity Monitoring 用于生物信号和人体活动监测的柔性可穿戴传感器网络

2014 11th International Conference on Wearable and Implantable Body Sensor Networks Workshops Pub Date : 2014-06-16 DOI: 10.1109/BSN.WORKSHOPS.2014.20

Ruben Dias, J. Machado da Silva

引用次数: 14

Head and Eye Movement as Pointing Modalities for Eyewear Computers 头眼运动作为眼镜电脑的指向方式

2014 11th International Conference on Wearable and Implantable Body Sensor Networks Workshops Pub Date : 2014-06-16 DOI: 10.1109/BSN.WORKSHOPS.2014.14

Shahram Jalaliniya, Diako Mardanbeigi, Thomas Pederson, D. Hansen

引用次数: 33

Energy Expenditure Estimation Using Accelerometry and Heart Rate for Multiple Sclerosis and Healthy Older Adults 利用加速计和心率估算多发性硬化症和健康老年人的能量消耗

2014 11th International Conference on Wearable and Implantable Body Sensor Networks Workshops Pub Date : 2014-06-16 DOI: 10.1109/BSN.WORKSHOPS.2014.18

A. Bourke, F. Massé, A. Arami, K. Aminian, M. Healy, J. Nelson, C. O'Dwyer, S. Coote

引用次数: 7

Comparative Study of Four Instrumented Mobility Analysis Tests on Neurological Disease Patients 四种仪器活动能力分析方法在神经系统疾病患者中的比较研究

2014 11th International Conference on Wearable and Implantable Body Sensor Networks Workshops Pub Date : 2014-06-16 DOI: 10.1109/BSN.WORKSHOPS.2014.13

A. Kuusik, K. Gross-Paju, Heigo Maamâgi, E. Reilent

引用次数: 4

Design and Development of an Inertial Sensor Based Exergame for Recovery-Step Training 基于惯性传感器的恢复步训练运动系统的设计与开发

2014 11th International Conference on Wearable and Implantable Body Sensor Networks Workshops Pub Date : 2014-06-16 DOI: 10.1109/BSN.WORKSHOPS.2014.16

A. Bourke, A. Barré, B. Mariani, Christopher Moufawad El Achkar, A. Paraschiv-Ionescu, K. Aminian, B. Vereijken, Nina Skjaeret, J. Helbostad

引用次数: 4

Characteristics of a Piezo-Resistive Fabric Stretch Sensor Glove for Home-Monitoring of Rheumatoid Arthritis 一种用于类风湿性关节炎家庭监测的压阻织物拉伸传感器手套的特性

2014 11th International Conference on Wearable and Implantable Body Sensor Networks Workshops Pub Date : 2014-06-16 DOI: 10.1109/BSN.WORKSHOPS.2014.15

Conor O'Quigley, M. Sabourin, S. Coyle, J. Connolly, Joan Condall, K. Curran, B. Corcoran, D. Diamond

引用次数: 20

Comparing Google Glass with Tablet-PC as Guidance System for Assembling Tasks 谷歌眼镜与平板电脑作为装配任务引导系统的比较

2014 11th International Conference on Wearable and Implantable Body Sensor Networks Workshops Pub Date : 2014-06-16 DOI: 10.1109/BSN.WORKSHOPS.2014.11

Matthias Wille, P. Scholl, S. Wischniewski, Kristof Van Laerhoven

引用次数: 24

User Interface Beaming -- Seamless Interaction with Smart Things Using Personal Wearable Computers

2014 11th International Conference on Wearable and Implantable Body Sensor Networks Workshops Pub Date : 2014-06-16 DOI: 10.1109/BSN.WORKSHOPS.2014.17

S. Mayer, G. Soros

引用次数: 36

Classification of Stair Ascent and Descent in Stroke Patients 脑卒中患者楼梯升降的分类

2014 11th International Conference on Wearable and Implantable Body Sensor Networks Workshops Pub Date : 2014-06-16 DOI: 10.1109/BSN.WORKSHOPS.2014.10

Kaspar Leuenberger, R. Gonzenbach, E. Wiedmer, A. Luft, R. Gassert

{"title":"Classification of Stair Ascent and Descent in Stroke Patients","authors":"Kaspar Leuenberger, R. Gonzenbach, E. Wiedmer, A. Luft, R. Gassert","doi":"10.1109/BSN.WORKSHOPS.2014.10","DOIUrl":"https://doi.org/10.1109/BSN.WORKSHOPS.2014.10","url":null,"abstract":"Wearable sensor units are a promising technology to assess ambulatory activities such as level walking, stair ascent and descent in the home environment, shedding light into the recovery process and independence of stroke survivors. However, algorithms for the identification of ambulatory activities were optimized for healthy subjects, and show limitations when considering the reduced walking speed and altered gait patterns found in patients. We present a method to identify ambulatory phases and distinguish stair ascent and descent from level walking in daily activity recordings of stroke survivors. A realistic dataset was captured with inertial and barometric pressure sensors worn at 5 anatomical locations. Statistical and wavelet based acceleration features fed into a Support Vector Machine were used to identify walking phases, while a k-Nearest-Neighbor classifier was used to discriminate between level walking, stair ascent and descent based on barometric pressure and acceleration features. Combining data from multiple sensor modules resulted in walking classification sensitivities and specificities of up to 96%. Looking at sensor modules individually, the module placed at the nonparetic ankle showed the best performance, increasing sensitivity of walking identification by almost 10% compared to the module at the paretic ankle. Level walking was identified with 97% sensitivity and 91% specificity, stair ascent with 94% sensitivity and 99% specificity and stair descent with 87% sensitivity and 99% specificity in the multi-sensor setup. Again, sensor modules placed at the ankles displayed the best performance when looking at modules individually.","PeriodicalId":311910,"journal":{"name":"2014 11th International Conference on Wearable and Implantable Body Sensor Networks Workshops","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123287335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 22