Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)最新文献_第7页

Grammar-based, posture- and context-cognitive detection for falls with different activity levels 基于语法、姿势和情境认知的不同活动水平跌倒检测

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2011-10-10 DOI: 10.1145/2077546.2077553

Qiang Li, J. Stankovic

{"title":"Grammar-based, posture- and context-cognitive detection for falls with different activity levels","authors":"Qiang Li, J. Stankovic","doi":"10.1145/2077546.2077553","DOIUrl":"https://doi.org/10.1145/2077546.2077553","url":null,"abstract":"Falls are dangerous for the aged population as they result in serious detrimental consequences. Therefore, many fall detection methods have been proposed. Most of these methods characterize falls by large accelerations and fast body orientation changes. However, certain activities like sitting down quickly, vigorous gaits, and jumping, also show these characteristics, and thus are hard to distinguish from real falls. Moreover, many falls in the elderly are slow falls which show lower activity levels. Existing work fails to detect slow falls effectively because they only identify falls with high activity levels.\u0000 In this paper, we present a grammar-based fall detection framework which not only better distinguishes fall-like activities from real falls, but also emphasizes the detection of slow falls. We utilize posture information extracted from on-body sensors and context information collected from sensors deployed in the house to reduce false positives. A fall in our framework is detected as a sequence of sensor events. We provide a context-free grammar to define these sequences so that the framework can be easily extended to detect more kinds of falls. Our case study shows that our method can distinguish various fall-like activities from real falls and can also effectively detect both fast falls and slow falls. The integration evaluation shows that our method achieves both high sensitivity and high specificity.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"64 1","pages":"6"},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86504532","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: 21

Lightweight power aware and scalable movement monitoring for wearable computers: a mining and recognition technique at the fingertip of sensors 用于可穿戴计算机的轻量级功率感知和可扩展运动监测:传感器指尖的挖掘和识别技术

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2011-10-10 DOI: 10.1145/2077546.2077554

Vitali Loseu, Jerry Mannil, R. Jafari

{"title":"Lightweight power aware and scalable movement monitoring for wearable computers: a mining and recognition technique at the fingertip of sensors","authors":"Vitali Loseu, Jerry Mannil, R. Jafari","doi":"10.1145/2077546.2077554","DOIUrl":"https://doi.org/10.1145/2077546.2077554","url":null,"abstract":"Activity monitoring using Body Sensor Networks(BSN) has gained much attention from the scientific community due to its recreational and medical applications. Suggested techniques for activity monitoring face two major problem. First, systems have to be trained for the individual subjects due to the heterogeneity of the BSN data. While most solutions can address this problem on a small data set, they have no mechanics for automatic scaling of the solution as the data set increases. Second, the battery limitations of the BSN severely limit the maximum deployment time for the continuous monitoring. This problem is often solved by shifting some processing to the local sensor nodes to avoid a very heavy communication cost. However, little work has been done to optimize the sensing and processing cost of the action recognition. In this paper, we propose an action recognition approach based on the BSN repository. We show how the information of a large repository can be automatically used to customize the processing on sensor nodes based on a limited and automated training process. We also investigate the power cost of such a repository mining approach on the sensor nodes based on our implementation. To assess the power requirement, we define an energy model for data sensing and processing. We demonstrate the relationship between the activity recognition precision and the power consumption of the system during continuous action monitoring. We demonstrate the energy effectiveness of our approach with a classification accuracy constraint based on limited data repository.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"91 1","pages":"7"},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89962450","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: 4

An ECG patch combining a customized ultra-low-power ECG SoC with Bluetooth low energy for long term ambulatory monitoring 结合定制的超低功耗ECG SoC和低功耗蓝牙的ECG贴片，用于长期动态监测

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2011-10-10 DOI: 10.1145/2077546.2077564

M. Altini, Salvatore Polito, J. Penders, Hyejung Kim, N. V. Helleputte, Sunyoung Kim, R. Yazicioglu

引用次数: 33

Feature extractors for integration of cameras and sensors during end-user programming of assistive monitoring systems 在辅助监控系统的最终用户编程过程中，用于集成摄像机和传感器的特征提取器

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2011-10-10 DOI: 10.1145/2077546.2077561

Alex D. Edgcomb, F. Vahid

引用次数: 2

Long-term monitoring of COPD using wearable sensors 使用可穿戴传感器长期监测COPD

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2011-10-10 DOI: 10.1145/2077546.2077568

Bor-rong Chen, Shyamal Patel, Luca Della Toffola, P. Bonato

{"title":"Long-term monitoring of COPD using wearable sensors","authors":"Bor-rong Chen, Shyamal Patel, Luca Della Toffola, P. Bonato","doi":"10.1145/2077546.2077568","DOIUrl":"https://doi.org/10.1145/2077546.2077568","url":null,"abstract":"Activity recognition can provide important contextual information for the diagnosis and treatment of several medical conditions. In COPD patients, measurement of long term physical activity level, combined with physiological parameters such as heart rate and respiration rate can be used for early detection of exacerbations. Using wearable sensors, we can achieve this goal by continuously monitoring the daily activities of COPD patients. Due to low computation power of wearable sensors, typical activity monitoring systems are designed to store or wirelessly transfer raw data from the sensors to a more powerful PC-class computer for classification. While this approach preserves the original data at the highest resolution, it is highly resource-intensive and therefore reduces the lifetime of the wearable sensors due to required storage space, bandwidth, and battery capacity. In this demo, we present an optimized activity monitoring system for COPD patients that performs feature extraction on wearable sensors. Such implementation minimizes the number of radio packets sent by the wearable sensors and eliminates the need to store raw sensor data.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"11 1","pages":"19"},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85333319","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

Rehabilitation exercise feedback on Android platform Android平台康复锻炼反馈

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2011-10-10 DOI: 10.1145/2077546.2077567

B. Caulfield, Jason Blood, Barry Smyth, D. Kelly

引用次数: 5

Converting body heat into reliable energy for powering physiological wireless sensors 将身体热量转化为可靠的能量，为生理无线传感器供电

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2011-10-10 DOI: 10.1145/2077546.2077580

I. Stark

引用次数: 12

Modeling human gait using a Kalman filter to measure walking distance 用卡尔曼滤波对人体步态进行建模以测量步行距离

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2011-10-10 DOI: 10.1145/2077546.2077584

K. Nagarajan, N. Gans, R. Jafari

引用次数: 9

mConverse: inferring conversation episodes from respiratory measurements collected in the field mConverse:从现场收集的呼吸测量数据推断谈话情节

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2011-10-10 DOI: 10.1145/2077546.2077557

Md. Mahbubur Rahman, A. Ali, K. Plarre, M. al’Absi, Emre Ertin, Santosh Kumar

{"title":"mConverse: inferring conversation episodes from respiratory measurements collected in the field","authors":"Md. Mahbubur Rahman, A. Ali, K. Plarre, M. al’Absi, Emre Ertin, Santosh Kumar","doi":"10.1145/2077546.2077557","DOIUrl":"https://doi.org/10.1145/2077546.2077557","url":null,"abstract":"Automated detection of social interactions in the natural environment has resulted in promising advances in organizational behavior, consumer behavior, and behavioral health. Progress, however, has been limited since the primary means of assessing social interactions today (i.e., audio recording) has several issues in field usage such as microphone occlusion, lack of speaker specificity, and high energy drain, in addition to significant privacy concerns.\u0000 In this paper, we present mConverse, a new mobile-based system to infer conversation episodes from respiration measurements collected in the field from an unobtrusively wearable respiratory inductive plethysmograph (RIP) band worn around the user's chest. The measurements are wire-lessly transmitted to a mobile phone, where they are used in a novel machine learning model to determine whether the wearer is speaking, listening, or quiet. Our model incorporates several innovations to address issues that naturally arise in the noisy field environment such as confounding events, poor data quality due to sensor loosening and detachment, losses in the wireless channel, etc. Our basic model obtains 83% accuracy for the three class classification. We formulate a Hidden Markov Model to further improve the accuracy to 87%. Finally, we apply our model to data collected from 22 subjects who wore the sensor for 2 full days in the field to observe conversation behavior in daily life and find that people spend 25% of their day in conversations.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"35 1","pages":"10"},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89391424","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: 53

Demonstration of sleep monitoring and caregiver displays for depression monitoring 睡眠监测的示范和抑郁症监测的看护人展示

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2011-10-10 DOI: 10.1145/2077546.2077571

Robert F. Dickerson, T. Hnat, Enamul Hoque, J. Stankovic

{"title":"Demonstration of sleep monitoring and caregiver displays for depression monitoring","authors":"Robert F. Dickerson, T. Hnat, Enamul Hoque, J. Stankovic","doi":"10.1145/2077546.2077571","DOIUrl":"https://doi.org/10.1145/2077546.2077571","url":null,"abstract":"We demonstrate a subset of the components used in a real-time depression monitoring product for the home. This system runs 24/7 and can potentially detect the early signs of a depression episode, as well as track progress managing a depressive illness. In the complete system, a cohesive set of integrated wireless sensors, a touch screen station, and associated software deliver the above capabilities. The data collected are multi-modal, spanning a number of different behavioral domains including sleep, weight, activities of daily living, and speech prosody. The reports generated by this aggregated data across multiple behavioral domains are aimed to provide caregivers with more accurate and thorough information about the patient's current functioning, thus helping in their diagnostic assessment and therapeutic treatment planning as well as for patients in the management and tracking of their symptoms. We show how the sleep monitoring module can collect bed movements to infer sleeping times and periods of restlessness, and we also present the caregiver display with its series of reports of patient emotional health.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"39 1","pages":"22"},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90592405","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