Pub Date : 2017-11-01DOI: 10.1109/HIC.2017.8227601
M. Al-Adhami, E. Tan, G. Rao, Y. Rostov
Highly sensitive device to detect bacteria in blood serum is presented. The device comprises of a microfluidic component and an electronic reader. The microfluidic cassette acts as an enclosed vial. It is filled with the sample after mixing with an indicator dye. Then, it is inserted into a kinetics fluorometer. The rate of the fluorescence increase is proportional to the number of viable cells in the sample. The fluorometer is portable. The device was tested with both lyophilized and fresh whole blood serums that were spiked with E.coli. Concentrations as low as 10 CFU/mL were detected. This paper discusses both the procedure to detect the bacteria as well as the results for different bacterial concentrations.
{"title":"A highly sensitive microfluidic device for bacterial detection in blood serum","authors":"M. Al-Adhami, E. Tan, G. Rao, Y. Rostov","doi":"10.1109/HIC.2017.8227601","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227601","url":null,"abstract":"Highly sensitive device to detect bacteria in blood serum is presented. The device comprises of a microfluidic component and an electronic reader. The microfluidic cassette acts as an enclosed vial. It is filled with the sample after mixing with an indicator dye. Then, it is inserted into a kinetics fluorometer. The rate of the fluorescence increase is proportional to the number of viable cells in the sample. The fluorometer is portable. The device was tested with both lyophilized and fresh whole blood serums that were spiked with E.coli. Concentrations as low as 10 CFU/mL were detected. This paper discusses both the procedure to detect the bacteria as well as the results for different bacterial concentrations.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125370345","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}
Pub Date : 2017-11-01DOI: 10.1109/HIC.2017.8227618
T. Ando, M. Hirano, Yu Ishige, S. Adachi
Precise dispensing of droplets is a crucial step for acquiring reliable diagnostic results. When a source sample volume is limited, the need for precise dispensing of submicroliter and nanoliter quantities is especially important. In this work, we developed a positive-displacement high-precision dispensing technique using a nickel electroformed tube with an inner diameter accuracy of 5 μm or less. When a dispensing variation of 100 nL was evaluated using a photometric method, the most stable coefficients of variation (CV) were observed for a tube thickness of 50 μm with hydrophobic treatment, where the average CV value was 1.3%. Furthermore, the glucose concentration in 200 nL of animal-based control serum was colorimetrically measured using enzymatic reactions without drying and mixing reagents. The CV value of the analysis was approximately 3%, suggesting that several biochemical panels can be precisely measured even from one drop of blood. The present positive-displacement dispenser ensures zero contamination and almost-zero dead volume and therefore would be useful for multi-panel clinical diagnosis.
{"title":"Precise dispensing technology for point-of-care diagnosis with micro-volume blood","authors":"T. Ando, M. Hirano, Yu Ishige, S. Adachi","doi":"10.1109/HIC.2017.8227618","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227618","url":null,"abstract":"Precise dispensing of droplets is a crucial step for acquiring reliable diagnostic results. When a source sample volume is limited, the need for precise dispensing of submicroliter and nanoliter quantities is especially important. In this work, we developed a positive-displacement high-precision dispensing technique using a nickel electroformed tube with an inner diameter accuracy of 5 μm or less. When a dispensing variation of 100 nL was evaluated using a photometric method, the most stable coefficients of variation (CV) were observed for a tube thickness of 50 μm with hydrophobic treatment, where the average CV value was 1.3%. Furthermore, the glucose concentration in 200 nL of animal-based control serum was colorimetrically measured using enzymatic reactions without drying and mixing reagents. The CV value of the analysis was approximately 3%, suggesting that several biochemical panels can be precisely measured even from one drop of blood. The present positive-displacement dispenser ensures zero contamination and almost-zero dead volume and therefore would be useful for multi-panel clinical diagnosis.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131155118","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}
Pub Date : 2017-11-01DOI: 10.1109/HIC.2017.8227608
B. Moatamed, Sajad Darabi, Migyeong Gwak, Mohammad Kachuee, Casey J. Metoyer, Mike Linn, M. Sarrafzadeh
Many coaches and athletes are showing an increasing interest in training monitoring systems every year. There is a plethora of performance markers that can aid in a coaches assessment of physiological and psychological conditions of their athletes. These markers can indicate an athletes readiness for competition, adaptation to training, or risk for injury. However, studies have shown examination of these performance markers individually may not result in a clear perception of ones performance. Hence, an inclusive analysis of these metrics is required to achieve meaningful assessment. Recently with the growing use of wearable activity trackers, we have access to many of these markers. Currently, there are a few sport monitoring tools which are using a subset of these metrics and are mostly providing real-time data visualization to coaching staff. However, an appropriate athletic performance monitoring system should be intuitive, provide useful data analysis, feedback and reliable predictions to coaches and athletes. In this paper, we are proposing an athletic monitoring system which collects a comprehensive set of metrics and visualize them in real-time and informs coaches about athlete's readiness score.
{"title":"Sport analytics platform for athletic readiness assessment","authors":"B. Moatamed, Sajad Darabi, Migyeong Gwak, Mohammad Kachuee, Casey J. Metoyer, Mike Linn, M. Sarrafzadeh","doi":"10.1109/HIC.2017.8227608","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227608","url":null,"abstract":"Many coaches and athletes are showing an increasing interest in training monitoring systems every year. There is a plethora of performance markers that can aid in a coaches assessment of physiological and psychological conditions of their athletes. These markers can indicate an athletes readiness for competition, adaptation to training, or risk for injury. However, studies have shown examination of these performance markers individually may not result in a clear perception of ones performance. Hence, an inclusive analysis of these metrics is required to achieve meaningful assessment. Recently with the growing use of wearable activity trackers, we have access to many of these markers. Currently, there are a few sport monitoring tools which are using a subset of these metrics and are mostly providing real-time data visualization to coaching staff. However, an appropriate athletic performance monitoring system should be intuitive, provide useful data analysis, feedback and reliable predictions to coaches and athletes. In this paper, we are proposing an athletic monitoring system which collects a comprehensive set of metrics and visualize them in real-time and informs coaches about athlete's readiness score.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131221633","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}
Pub Date : 2017-11-01DOI: 10.1109/HIC.2017.8227606
Marisa Walker, Weiwei Ge, J. Gichoya, S. Purkayastha
The use of clinical practice guidelines to improve quality of care has been a vividly discussed topic. Clinical practice guidelines (CPG) aim to improve the health of patients by guiding individual care in clinical settings. CPGs bring potential benefits for patients by improving clinical decision making, improving efficiency and enhancing patient care, while essentially optimizing financial value. Chronic conditions like heart disease, stroke, and chronic obstructive pulmonary disease (COPD), plague the US healthcare system causing several million dollars in healthcare related cost. This paper demonstrates the development of a CPG into an open-source EHR system to effectively manage COPD patients. The CPG is incorporated using the open web app standard, which allows it to be used with any web browser based EHR system, once data from the EHR system can be fed into the app. As a result, the CPG helps create a more effective and efficient decision-making process.
{"title":"Implementing clinical practice guidelines for chronic obstructive pulmonary disease in an EHR system","authors":"Marisa Walker, Weiwei Ge, J. Gichoya, S. Purkayastha","doi":"10.1109/HIC.2017.8227606","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227606","url":null,"abstract":"The use of clinical practice guidelines to improve quality of care has been a vividly discussed topic. Clinical practice guidelines (CPG) aim to improve the health of patients by guiding individual care in clinical settings. CPGs bring potential benefits for patients by improving clinical decision making, improving efficiency and enhancing patient care, while essentially optimizing financial value. Chronic conditions like heart disease, stroke, and chronic obstructive pulmonary disease (COPD), plague the US healthcare system causing several million dollars in healthcare related cost. This paper demonstrates the development of a CPG into an open-source EHR system to effectively manage COPD patients. The CPG is incorporated using the open web app standard, which allows it to be used with any web browser based EHR system, once data from the EHR system can be fed into the app. As a result, the CPG helps create a more effective and efficient decision-making process.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124778517","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}
Pub Date : 2017-11-01DOI: 10.1109/HIC.2017.8227626
Jairo Maldonado-Contreras, P. Marayong, I-Hung Khoo, Rae Rivera, Brian Ruhe, Will Wu
Limited mobility severely impacts the quality of life of persons with lower-limb amputations. Therefore, it is imperative to develop proper rehabilitation techniques to prevent falls and injuries. A vibrotactile device was developed as a training tool to enhance the rehabilitation of persons with recent lower-limb amputations. Stimuli provided by the device trains the user to sense discrete perturbations and then perform a corrective movement to reduce the chance of a fall. This pilot study was conducted to test the functionality of the device in improving the prosthetic proprioception of lower-limb amputees and the effect of the training instruction on motor learning. Two subjects were included in this study, one control and one receiving experimental training, with both subjects performing standing and walking tasks. Standing trials were used to evaluate the improvements in response and movement times and walking trials were tested for improvements in correct movement. In the standing task, the control and the experimental subject showed a 0.1% and 17% improvement in response time, respectively. In the walking task, both subjects showed improvements in making correct movement. Future work will focus on the design improvements of the device and the experiment protocols to further evaluate the effectiveness of the training.
{"title":"Proprioceptive improvements of lower-limb amputees under training with a vibrotactile device — A pilot study","authors":"Jairo Maldonado-Contreras, P. Marayong, I-Hung Khoo, Rae Rivera, Brian Ruhe, Will Wu","doi":"10.1109/HIC.2017.8227626","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227626","url":null,"abstract":"Limited mobility severely impacts the quality of life of persons with lower-limb amputations. Therefore, it is imperative to develop proper rehabilitation techniques to prevent falls and injuries. A vibrotactile device was developed as a training tool to enhance the rehabilitation of persons with recent lower-limb amputations. Stimuli provided by the device trains the user to sense discrete perturbations and then perform a corrective movement to reduce the chance of a fall. This pilot study was conducted to test the functionality of the device in improving the prosthetic proprioception of lower-limb amputees and the effect of the training instruction on motor learning. Two subjects were included in this study, one control and one receiving experimental training, with both subjects performing standing and walking tasks. Standing trials were used to evaluate the improvements in response and movement times and walking trials were tested for improvements in correct movement. In the standing task, the control and the experimental subject showed a 0.1% and 17% improvement in response time, respectively. In the walking task, both subjects showed improvements in making correct movement. Future work will focus on the design improvements of the device and the experiment protocols to further evaluate the effectiveness of the training.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124233472","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}
Pub Date : 2017-11-01DOI: 10.1109/HIC.2017.8227595
Si Mon Kueh, T. Kazmierski
This paper outlines the feasibility of detecting epilepsy though low-cost and low-energy dedicated hardware with bit-serial processing. The concept of a novel bit-serial data processing unit (DPU) is presented which implements the functionality of a complete neuron. The proposed approach has been tested using various network configurations and compared with related work. The proposed DPU uses only 24 Adaptive Logic Modules on an Altera Cyclone V FPGA. An array of these DPUs are controlled by a simple finite state machine. The proposed DPU allows the construction of complex hardware ANNs that can be implemented in portable equipment that suits the needs of a single epileptic patient in his or her daily activities to detect impending seizure events.
本文概述了利用低成本、低能耗的专用硬件进行位串行处理检测癫痫的可行性。提出了一种实现完整神经元功能的新型位串行数据处理单元(DPU)的概念。该方法已在不同的网络配置下进行了测试，并与相关工作进行了比较。提出的DPU在Altera Cyclone V FPGA上仅使用24个自适应逻辑模块。这些dpu的数组由一个简单的有限状态机控制。提出的DPU允许构建复杂的硬件人工神经网络，可以在便携式设备中实现，以满足单个癫痫患者在其日常活动中检测即将发生的癫痫事件的需要。
{"title":"A dedicated bit-serial hardware neuron for massively-parallel neural networks in fast epilepsy diagnosis","authors":"Si Mon Kueh, T. Kazmierski","doi":"10.1109/HIC.2017.8227595","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227595","url":null,"abstract":"This paper outlines the feasibility of detecting epilepsy though low-cost and low-energy dedicated hardware with bit-serial processing. The concept of a novel bit-serial data processing unit (DPU) is presented which implements the functionality of a complete neuron. The proposed approach has been tested using various network configurations and compared with related work. The proposed DPU uses only 24 Adaptive Logic Modules on an Altera Cyclone V FPGA. An array of these DPUs are controlled by a simple finite state machine. The proposed DPU allows the construction of complex hardware ANNs that can be implemented in portable equipment that suits the needs of a single epileptic patient in his or her daily activities to detect impending seizure events.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114911835","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}
Pub Date : 2017-11-01DOI: 10.1109/HIC.2017.8227571
W. Boonchieng, E. Boonchieng, W. Tuanrat, Chatchai Khuntichot, K. Duangchaemkarn
Home care service is an important sector of public health service in Thailand. It is necessary that home healthcare team needed to access patient past medical history to improve the overall quality of the service. However, the limitation of current electronics health record (EHR) system, patient medical record is unable to access outside the healthcare setting. We developed a virtual electronic health record and integrated it into the community-based health determinant data system which is containing health-related determinant information range from district level down to individual level, based on the location of their household. The aim of this project is to develop an integrated system that can reconcile the medical history from the hospital to provide intuitive information for the home healthcare team. According to this objective, transmission control protocol and internet protocol (TCP/IP) architecture was designed and developed. Different independent databases are connected using mobile communication platform (mHealth). User authorization requires to retrieve the individual clinical information from virtual EHR. The evaluation of mHealth application based on usability tests and feasibility studies on effectiveness, efficacy, and satisfaction for home healthcare providers.
{"title":"Integrative system of virtual electronic health record with online community-based health determinant data for home care service: MHealth development and usability test","authors":"W. Boonchieng, E. Boonchieng, W. Tuanrat, Chatchai Khuntichot, K. Duangchaemkarn","doi":"10.1109/HIC.2017.8227571","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227571","url":null,"abstract":"Home care service is an important sector of public health service in Thailand. It is necessary that home healthcare team needed to access patient past medical history to improve the overall quality of the service. However, the limitation of current electronics health record (EHR) system, patient medical record is unable to access outside the healthcare setting. We developed a virtual electronic health record and integrated it into the community-based health determinant data system which is containing health-related determinant information range from district level down to individual level, based on the location of their household. The aim of this project is to develop an integrated system that can reconcile the medical history from the hospital to provide intuitive information for the home healthcare team. According to this objective, transmission control protocol and internet protocol (TCP/IP) architecture was designed and developed. Different independent databases are connected using mobile communication platform (mHealth). User authorization requires to retrieve the individual clinical information from virtual EHR. The evaluation of mHealth application based on usability tests and feasibility studies on effectiveness, efficacy, and satisfaction for home healthcare providers.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129318062","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}
Pub Date : 2017-11-01DOI: 10.1109/HIC.2017.8227588
Mohsen Nabian, A. Nouhi, Yu Yin, S. Ostadabbas
Electrocardiogram (ECG), Electrodermal Activity (EDA), Electromyogram (EMG) and Impedance Cardiography (ICG) are among physiological signals widely used in various biomedical applications including health tracking, sleep quality assessment, early disease detection/diagnosis and human affective state recognition. This paper presents the development of a biosignal-specific processing and feature extraction tool for analyzing these physiological signals according to the state-of-the-art studies reported in the scientific literature. This tool is intended to assist researchers in machine learning and pattern recognition to extract feature matrix from these bio-signals automatically and reliably. In this paper, we provided the algorithms used for the signal-specific filtering and segmentation as well as extracting features that have been shown highly relevant to a better category discrimination in an intended application. This tool is an open-source software written in MATLAB and made compatible with MathWorks Classification Learner app for further classification purposes such as model training, cross-validation scheme farming, and classification result computation.
{"title":"A biosignal-specific processing tool for machine learning and pattern recognition","authors":"Mohsen Nabian, A. Nouhi, Yu Yin, S. Ostadabbas","doi":"10.1109/HIC.2017.8227588","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227588","url":null,"abstract":"Electrocardiogram (ECG), Electrodermal Activity (EDA), Electromyogram (EMG) and Impedance Cardiography (ICG) are among physiological signals widely used in various biomedical applications including health tracking, sleep quality assessment, early disease detection/diagnosis and human affective state recognition. This paper presents the development of a biosignal-specific processing and feature extraction tool for analyzing these physiological signals according to the state-of-the-art studies reported in the scientific literature. This tool is intended to assist researchers in machine learning and pattern recognition to extract feature matrix from these bio-signals automatically and reliably. In this paper, we provided the algorithms used for the signal-specific filtering and segmentation as well as extracting features that have been shown highly relevant to a better category discrimination in an intended application. This tool is an open-source software written in MATLAB and made compatible with MathWorks Classification Learner app for further classification purposes such as model training, cross-validation scheme farming, and classification result computation.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129343235","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}
Pub Date : 2017-11-01DOI: 10.1109/HIC.2017.8227593
A. Samadani, D. Schulman, Portia E. Singh, Mladen Milošević
Personal emergency response systems (PERS) such as Philips Lifeline help seniors maintain independence and age in place. PERS can use predictive analytics to help risk stratification and promote response-efficient emergency services. This paper presents a framework for estimating significant associations between Lifeline user characteristics and occurrence of emergency events. Predictive variables including demographics, health conditions, environmental, and user-specific lifeline history were identified and their associations to emergency events were delineated. The predictive variables can help with 1) identifying individuals at high risk and 2) management and prioritization of care and preventive services, which can result in reducing adverse health events and improving user's quality of life.
{"title":"Association rule mining for risk prediction and stratification: A philips lifeline case study","authors":"A. Samadani, D. Schulman, Portia E. Singh, Mladen Milošević","doi":"10.1109/HIC.2017.8227593","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227593","url":null,"abstract":"Personal emergency response systems (PERS) such as Philips Lifeline help seniors maintain independence and age in place. PERS can use predictive analytics to help risk stratification and promote response-efficient emergency services. This paper presents a framework for estimating significant associations between Lifeline user characteristics and occurrence of emergency events. Predictive variables including demographics, health conditions, environmental, and user-specific lifeline history were identified and their associations to emergency events were delineated. The predictive variables can help with 1) identifying individuals at high risk and 2) management and prioritization of care and preventive services, which can result in reducing adverse health events and improving user's quality of life.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125691869","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}
Pub Date : 2017-11-01DOI: 10.1109/HIC.2017.8227614
E. Pino, Javier A. P. Chávez, P. Aqueveque
Ballistocardiogram (BCG) has been revisited in the last years as an unobtrusive method to detect heart beats. New electromechanical film (EMFi) sensors are now able to detect minimal oscillations in its surface, allowing to detect the mechanical action of the heart as it beats. This has allowed to develop unobtrusive systems for heart rate monitoring to be used as Point-of-Care devices, and to deploy them in waiting rooms, assisted living facilities or at home. In this work, an EMFi sensor is used to measure BCG via the pressure changes on the seat produced by the beating heart. In a lab environment, 34 healthy volunteers are measured under two conditions: at rest and after exercise, simultaneously with ECG. Also, in a clinical environment, 24 volunteers are also measured while waiting. The algorithm looks for the variability of the length transform at different scales or windows to determine a search window to detect beats from the BCG. A second correlation filter helps eliminate false peaks detected due to noise in the signal. Results show that in resting conditions, the mean error between the BCG HR and the reference ECG is only 0.4 beats per minute, with a standard deviation of 1.88. The noise rejection accuracy is 93%. The proposed algorithm can be used to identify beats and issue alarms under abnormal rhythms, providing timely alerts for at-risk population.
{"title":"BCG algorithm for unobtrusive heart rate monitoring","authors":"E. Pino, Javier A. P. Chávez, P. Aqueveque","doi":"10.1109/HIC.2017.8227614","DOIUrl":"https://doi.org/10.1109/HIC.2017.8227614","url":null,"abstract":"Ballistocardiogram (BCG) has been revisited in the last years as an unobtrusive method to detect heart beats. New electromechanical film (EMFi) sensors are now able to detect minimal oscillations in its surface, allowing to detect the mechanical action of the heart as it beats. This has allowed to develop unobtrusive systems for heart rate monitoring to be used as Point-of-Care devices, and to deploy them in waiting rooms, assisted living facilities or at home. In this work, an EMFi sensor is used to measure BCG via the pressure changes on the seat produced by the beating heart. In a lab environment, 34 healthy volunteers are measured under two conditions: at rest and after exercise, simultaneously with ECG. Also, in a clinical environment, 24 volunteers are also measured while waiting. The algorithm looks for the variability of the length transform at different scales or windows to determine a search window to detect beats from the BCG. A second correlation filter helps eliminate false peaks detected due to noise in the signal. Results show that in resting conditions, the mean error between the BCG HR and the reference ECG is only 0.4 beats per minute, with a standard deviation of 1.88. The noise rejection accuracy is 93%. The proposed algorithm can be used to identify beats and issue alarms under abnormal rhythms, providing timely alerts for at-risk population.","PeriodicalId":120815,"journal":{"name":"2017 IEEE Healthcare Innovations and Point of Care Technologies (HI-POCT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131386189","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}
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