Purpose:The purpose of this study was to compare established methods with newly-developed methods for estimating the total energy expenditure(TEE). Methods:The study subjects comprised 46 individuals,including 16 midd...Purpose:The purpose of this study was to compare established methods with newly-developed methods for estimating the total energy expenditure(TEE). Methods:The study subjects comprised 46 individuals,including 16 middle-aged men(mean age 51.4 years),14 middle-aged women(mean age 49.9 years) and 16 young women(mean age 19.1 years).The TEE was estimated from 24-h heart rate(HR) data using newly-developed software (MoveSense HRAnalyzer 201 la,RC1.Suunto Oy,Vantaa,Finland),and was compared against the TEE determined using doubly labeled water (DLW).Agreement between the two methods was analyzed using Bland and Altman plots. Results:The HR method yielded similar TEE values as the DLW method at the group level,with an average of 8.6 kcal/day in the difference in the mean,but with large individual variations.Forty-four(96%) out of 46 subjects fell within±2SD of the mean difference in TEE comparisons, and there was no tendency towards under- or over-estimation. Conclusion:Our results indicate that the current software using HR analysis for the estimation of daily TEE needs further development for use with free-living individuals.展开更多
Heart failure (HF) is an emerging epidemic associate with significant morbidity, mortality, and health care expenditure. Although there were major advances in pharmacologic and device based therapies for the managemen...Heart failure (HF) is an emerging epidemic associate with significant morbidity, mortality, and health care expenditure. Although there were major advances in pharmacologic and device based therapies for the management of HF, mortality of this condition remains high. Accurate monitoring of HF patients for exacerbations is very important to reduce recurrent hospitalizations and its associated complications. With the failure of clinical signs, tele-monitoring, and laboratory bio-markers to function as early markers of HF exacerbations, more sophisticated techniques were sought to accurately predict the circulatory status in HF patients in order to execute timely pharmacological intervention to reduce frequent hospitalizations. CardioMEMS<sup>TM</sup> (St. Jude Medical, Inc., Saint Paul, Minnesota) is an implantable, wireless pulmonary arterial pressure (PAP) monitoring system which transmits the patient’s continuous PAPs to the treating health care provider in the ambulatory setting. PAP-guided medical therapy modification has been shown to significantly reduce HF-related hospitalization and overall mortality. In advanced stages of HF, wireless access to hemodynamic information correlated with earlier left ventricular assist device implantation and shorter time to heart transplantation.展开更多
A method and apparatus for monitoring heart rate of the heart using a wearable system is designed and implemented in this paper. A heart rate receives from heart beat signals and stores the data to a database and afte...A method and apparatus for monitoring heart rate of the heart using a wearable system is designed and implemented in this paper. A heart rate receives from heart beat signals and stores the data to a database and after a time period this method can determine an idle heart rate of the monitoring body. This idle heart rate is compared with the stored data and can determine the normal and abnormal heart rate variability. After the certain time period this system can detect the heart rate and also can send a signal to the user in time of abnormalities. Consequent estimations of heart rate variability are contrasted with this.展开更多
This paper proposes a batteryless sensing and computational device to collect and process electrocardiography(ECG)signals for monitoring heart rate variability(HRV).The proposed system comprises of a passive UHF radio...This paper proposes a batteryless sensing and computational device to collect and process electrocardiography(ECG)signals for monitoring heart rate variability(HRV).The proposed system comprises of a passive UHF radio frequency identification(RFID)tag,an extreme low power microcontroller,a low-power ECG circuit,and a radio frequency(RF)energy harvester.The microcontroller and ECG circuits consume less power of only~30μA and~3 mA,respectively.Therefore,the proposed RF harvester operating at frequency band of 902 MHz~928 MHz can sufficiently collect available energy from the RFID reader to supply power to the system within a maximum distance of~2 m.To extract R-peak of the ECG signal,a robust algorithm that consumes less time processing is also developed.The information of R-peaks is stored into an Electronic Product Code(EPC)Class 1st Generation 1st compliant ID of the tag and read by the reader.This reader is functioned to collected the R-peak data with sampling rate of 100ms;therefore,the user application can monitor fully range of HRV.The performance of the proposed system shows that this study can provide a good solution in paving the way to new classes of healthcare applications.展开更多
In this paper, we introduce a system architecture for a patient centered mobile health monitoring (PCMHM) system that deploys different sensors to determine patients’ activities, medical conditions, and the cause of ...In this paper, we introduce a system architecture for a patient centered mobile health monitoring (PCMHM) system that deploys different sensors to determine patients’ activities, medical conditions, and the cause of an emergency event. This system combines and analyzes sensor data to produce the patients’ detailed health information in real-time. A central computational node with data analyzing capability is used for sensor data integration and analysis. In addition to medical sensors, surrounding environmental sensors are also utilized to enhance the interpretation of the data and to improve medical diagnosis. The PCMHM system has the ability to provide on-demand health information of patients via the Internet, track real-time daily activities and patients’ health condition. This system also includes the capability for assessing patients’ posture and fall detection.展开更多
Objective:To make and study computed system for external cardiac massage,monitor of heart and body temperature and observe its clinical effect.Method:The system was made and applied.Result:The effect of system was obv...Objective:To make and study computed system for external cardiac massage,monitor of heart and body temperature and observe its clinical effect.Method:The system was made and applied.Result:The effect of system was obvious.Conclusion: The system was an effective clinical equipment in treatment of patient with cardiac arrest.展开更多
Cardiovascular diseases remain a leading global cause of mortality,underscoring the urgent need for intelligent diagnostic tools to enhance early detection,prediction,diagnosis,prevention,treatment,and recovery.This d...Cardiovascular diseases remain a leading global cause of mortality,underscoring the urgent need for intelligent diagnostic tools to enhance early detection,prediction,diagnosis,prevention,treatment,and recovery.This demand has spurred the advancement of wearable and flexible technologies,revolutionizing continuous,noninvasive,and remote heart sound(HS)monitoring—a vital avenue for assessing heart activity.The conventional stethoscope,used to listen to HSs,has limitations in terms of its physical structure,as it is inflexible and bulky,which restricts its prospective applications.Recently,mechanoacoustic sensors have made remarkable advancements,evolving from primitive forms to soft,flexible,and wearable designs.This article provides an in-depth review of the latest scientific and technological advancements by addressing various topics,including different types of sensors,sensing materials,design principles,denoising techniques,and clinical applications of flexible and wearable HS sensors.This transformative potential lies in the capacity for ongoing,remote,and personalized monitoring,promising enhanced patient outcomes,amplified remote monitoring capabilities,and timely diagnoses.Last,the article highlights current challenges and prospects for the future,suggesting techniques to advance HS sensing technologies for exciting real‐time applications.展开更多
Wearable photodetectors have come under the limelight of optoelectronic technologies on account of multiple advantages spanning light weight,easy-portability,excellent bendability,outstanding conformability,etc.Among ...Wearable photodetectors have come under the limelight of optoelectronic technologies on account of multiple advantages spanning light weight,easy-portability,excellent bendability,outstanding conformability,etc.Among diverse candidate materials,low-dimensional van der Waals materials(LDvdWMs)have emerged to be preeminent owing to the dangling-bond-free surface,exceptional carrier mobility,nanoscale dimensionality,and excellent light-harvesting capability.However,to date,the majority of flexible LDvdWM photodetectors have been fabricated through exfoliation-,transfer-,or solution-processing methods,which are plagued by limitations such as low production yield,inadequate photosensitivity,and sluggish response rate.Thus far,constructing LDvdWM photodetectors in situ on flexible substrates remains quite challenging due to the irreconcilable contradiction between the weak robustness of flexible polymer substrates against high temperature and the large thermal budget required for crystallization.This study develops scalable preparation of Sb_(2)Se_(3)nanofilm directly on flexible polyimide substrates by exploiting pulsed-laser deposition(PLD),where highly energetic species can be generated to enable overcoming the reaction barrier for crystallization at a relatively low temperature.The corresponding Sb_(2)Se_(3)photodetectors have exhibited high responsivity of 1.15 A/W,exceptional external quantum efficiency of 269%,and impressive specific detectivity reaching 2.4×10^(11)Jones,coupled with swift switching characteristics.Importantly,excellent durability to repeated bending treatments has been confirmed by the consistent photoresponse over 500 convex/concave bending cycles.Furthermore,the device has showcased strong robustness against extrinsic impinging.In the end,by using Sb_(2)Se_(3)photodetectors as sensing components,wide-band imaging beyond human vision and heart rate monitoring have been realized.This study has underscored the high efficacy of PLD for reconciling the long-standing contradiction between the weak robustness of flexible polymer substrates against high temperature and the substantial thermal energy required for crystallization,opening new opportunities towards next-generation wearable optoelectronic industry.展开更多
With the increasing aging population and personalized health management needs,this paper proposes an IoT-based home heart rate monitoring system.The system uses the STM32 microcontroller as the core,integrating a PPG ...With the increasing aging population and personalized health management needs,this paper proposes an IoT-based home heart rate monitoring system.The system uses the STM32 microcontroller as the core,integrating a PPG sensor and a body temperature sensor to collect physiological data such as heart rate,blood oxygen saturation,and body temperature.The data is transmitted in real-time to the server and mobile application via the ESP8266 module.Users can view historical data,set alarm thresholds,and re ceive alerts through sound alarms and push notifications when abnormalities are detected.The test results show that the heart rate measurement error is less than 5%,verifying the practicality and reliability of the system in home healt h monitoring and ch ronic disease prevention.This research provides a cost-effective solution for home users who require convenient and continuous health monitoring,especially for the elderly and patients with chronic diseases.展开更多
A low power wavelet denoising chip for photoplethysmography （PPG） detection and portable heart rate monitoring is presented. To eliminate noise and improve detection accuracy, Harr wavelet （HWT） is chosen as the p...A low power wavelet denoising chip for photoplethysmography （PPG） detection and portable heart rate monitoring is presented. To eliminate noise and improve detection accuracy, Harr wavelet （HWT） is chosen as the processing tool. An optimized finite impulse response structure is proposed to lower the computational complexity of proposed algorithm, which is benefit for reducing the power consumption of proposed chip. The modulus max- ima pair location module is design to accurately locate the PPG peaks. A clock control unit is designed to further reduce the power consumption of the proposed chip. Fabricated with the 0.18μm N-well CMOS 1P6M technol- ogy, the power consumption of proposed chip is only 8.12μW in 1 V voltage supply. Validated with PPG signals in multiparameter intelligent monitoring in intensive care databases and signals acquired by the wrist photoelectric volume detection front end, the proposed chip can accurately detect PPG signals. The average sensitivity and positive prediction are 99.91% and 100%, respectively.展开更多
The singlemode-multimode-singlemode(SMS)fiber structure for a heart rate monitoring is proposed and developed.An artificial electrocardiogram(ECG)signal is used to simulate the heart pulse at different rates ranging f...The singlemode-multimode-singlemode(SMS)fiber structure for a heart rate monitoring is proposed and developed.An artificial electrocardiogram(ECG)signal is used to simulate the heart pulse at different rates ranging from 50 beats per minute(bpm)to 200 bpm.The SMS fiber structure is placed at the center of a loudspeaker and it senses the vibration of the pulse.The vibration of the pulse signal applied to the SMS fiber structure changes the intensity of the optical output power.The proposed sensor shows a linear frequency of the heart rate sensing range that matches well with the relevant heart rate from the artificial ECG.This work shows the capability of the SMS fiber structure monitoring the heart rate frequencies for a long term,high stability realization,and reproducibility,and being suitable for the observation in hospitals as well as in other environments.展开更多
Fatigue impairs workers’judgment,reduces their productivity,and jeopardizes their safety.The paper presents a tool to predict workers’fatigue based on their vital signs.An experimental study was conducted in w...Fatigue impairs workers’judgment,reduces their productivity,and jeopardizes their safety.The paper presents a tool to predict workers’fatigue based on their vital signs.An experimental study was conducted in which the heart rate and sleep quality for three individuals were monitored using fitness trackers(wearable sensors).The data collected were used to develop two models based on regression analysis and Artificial Neural Networks(ANN),to predict their fatigue level.A Borg’s scale was used to estimate the Rating of Perceived Exertion(RPE)of the participants.The two models were able to satisfactorily predict the RPE(workers fatigue level)with an average validity of 75%and 80%for the regression ANN models,respectively.The developed models can provide project managers and superintendents with early warning to avoid potential worker overexertion,injuries,and fatalities.展开更多
Leveraging the power of artificial intelligence to facilitate an automatic analysis and monitoring of heart sounds has increasingly attracted tremendous efforts in the past decade.Nevertheless,lacking on standard open...Leveraging the power of artificial intelligence to facilitate an automatic analysis and monitoring of heart sounds has increasingly attracted tremendous efforts in the past decade.Nevertheless,lacking on standard open-access database made it difficult to maintain a sustainable and comparable research before the first release of the PhysioNet CinC Challenge Dataset.However,inconsistent standards on data collection,annotation,and partition are still restraining a fair and efficient comparison between different works.To this line,we introduced and benchmarked a first version of the Heart Sounds Shenzhen(HSS)corpus.Motivated and inspired by the previous works based on HSS,we redefined the tasks and make a comprehensive investigation on shallow and deep models in this study.First,we segmented the heart sound recording into shorter recordings(10 s),which makes it more similar to the human auscultation case.Second,we redefined the classification tasks.Besides using the 3 class categories(normal,moderate,and mild/severe)adopted in HSS,we added a binary classification task in this study,i.e.,normal and abnormal.In this work,we provided detailed benchmarks based on both the classic machine learning and the state-of-the-art deep learning technologies,which are reproducible by using open-source toolkits.Last but not least,we analyzed the feature contributions of best performance achieved by the benchmark to make the results more convincing and interpretable.展开更多
During surgery,a heartbeat doesn’t just tell whether a person is dead or alive-it can warn of big problems that come up quite suddenly.Keeping watch for subtle irregularities in the heart’s electric activity can hel...During surgery,a heartbeat doesn’t just tell whether a person is dead or alive-it can warn of big problems that come up quite suddenly.Keeping watch for subtle irregularities in the heart’s electric activity can help save a patient’s life.But today’s technology can’t give as much detail as doctors展开更多
基金funded by the Academy of Finlandthe Finnish Ministry of Education,Suunto Oy+2 种基金the Shanghai overseas distinguish professor award program 2011the Shanghai Key Lab of Human Performance(No.11DZ2261100)2012 National Science and Technology Infrastructure Program(Grant No. 2012BAK21B00).
文摘Purpose:The purpose of this study was to compare established methods with newly-developed methods for estimating the total energy expenditure(TEE). Methods:The study subjects comprised 46 individuals,including 16 middle-aged men(mean age 51.4 years),14 middle-aged women(mean age 49.9 years) and 16 young women(mean age 19.1 years).The TEE was estimated from 24-h heart rate(HR) data using newly-developed software (MoveSense HRAnalyzer 201 la,RC1.Suunto Oy,Vantaa,Finland),and was compared against the TEE determined using doubly labeled water (DLW).Agreement between the two methods was analyzed using Bland and Altman plots. Results:The HR method yielded similar TEE values as the DLW method at the group level,with an average of 8.6 kcal/day in the difference in the mean,but with large individual variations.Forty-four(96%) out of 46 subjects fell within±2SD of the mean difference in TEE comparisons, and there was no tendency towards under- or over-estimation. Conclusion:Our results indicate that the current software using HR analysis for the estimation of daily TEE needs further development for use with free-living individuals.
文摘Heart failure (HF) is an emerging epidemic associate with significant morbidity, mortality, and health care expenditure. Although there were major advances in pharmacologic and device based therapies for the management of HF, mortality of this condition remains high. Accurate monitoring of HF patients for exacerbations is very important to reduce recurrent hospitalizations and its associated complications. With the failure of clinical signs, tele-monitoring, and laboratory bio-markers to function as early markers of HF exacerbations, more sophisticated techniques were sought to accurately predict the circulatory status in HF patients in order to execute timely pharmacological intervention to reduce frequent hospitalizations. CardioMEMS<sup>TM</sup> (St. Jude Medical, Inc., Saint Paul, Minnesota) is an implantable, wireless pulmonary arterial pressure (PAP) monitoring system which transmits the patient’s continuous PAPs to the treating health care provider in the ambulatory setting. PAP-guided medical therapy modification has been shown to significantly reduce HF-related hospitalization and overall mortality. In advanced stages of HF, wireless access to hemodynamic information correlated with earlier left ventricular assist device implantation and shorter time to heart transplantation.
文摘A method and apparatus for monitoring heart rate of the heart using a wearable system is designed and implemented in this paper. A heart rate receives from heart beat signals and stores the data to a database and after a time period this method can determine an idle heart rate of the monitoring body. This idle heart rate is compared with the stored data and can determine the normal and abnormal heart rate variability. After the certain time period this system can detect the heart rate and also can send a signal to the user in time of abnormalities. Consequent estimations of heart rate variability are contrasted with this.
基金supported by FPT University,Hanoi,Vietnamand Nguyen Tat Thanh University,Ho Chi Minh City,Vietnam.
文摘This paper proposes a batteryless sensing and computational device to collect and process electrocardiography(ECG)signals for monitoring heart rate variability(HRV).The proposed system comprises of a passive UHF radio frequency identification(RFID)tag,an extreme low power microcontroller,a low-power ECG circuit,and a radio frequency(RF)energy harvester.The microcontroller and ECG circuits consume less power of only~30μA and~3 mA,respectively.Therefore,the proposed RF harvester operating at frequency band of 902 MHz~928 MHz can sufficiently collect available energy from the RFID reader to supply power to the system within a maximum distance of~2 m.To extract R-peak of the ECG signal,a robust algorithm that consumes less time processing is also developed.The information of R-peaks is stored into an Electronic Product Code(EPC)Class 1st Generation 1st compliant ID of the tag and read by the reader.This reader is functioned to collected the R-peak data with sampling rate of 100ms;therefore,the user application can monitor fully range of HRV.The performance of the proposed system shows that this study can provide a good solution in paving the way to new classes of healthcare applications.
文摘In this paper, we introduce a system architecture for a patient centered mobile health monitoring (PCMHM) system that deploys different sensors to determine patients’ activities, medical conditions, and the cause of an emergency event. This system combines and analyzes sensor data to produce the patients’ detailed health information in real-time. A central computational node with data analyzing capability is used for sensor data integration and analysis. In addition to medical sensors, surrounding environmental sensors are also utilized to enhance the interpretation of the data and to improve medical diagnosis. The PCMHM system has the ability to provide on-demand health information of patients via the Internet, track real-time daily activities and patients’ health condition. This system also includes the capability for assessing patients’ posture and fall detection.
文摘Objective:To make and study computed system for external cardiac massage,monitor of heart and body temperature and observe its clinical effect.Method:The system was made and applied.Result:The effect of system was obvious.Conclusion: The system was an effective clinical equipment in treatment of patient with cardiac arrest.
基金supported by the City University of Hong Kong and funded by the Research Grants Council(RGC)partly supported by the InnoHK Project on Project 1.2-Novel Drug Delivery Systems to Achieve Precision Medicine for Acute CVD Patients(a closed-loop CVD control system)at the Hong Kong Center for Cerebrocardiovascular Health Engineering(COCHE).City University of Hong Kong(9610430,7006082,9678292,7020073,9609332,9609333),funded by the Research Grants Council(RGC)+2 种基金Innovation and Technology Commission(ITC)(9667220)-Research Talent Hub(RTH)1-5University Grant Committee(UGC)Innovation and Technology Fund(ITF).
文摘Cardiovascular diseases remain a leading global cause of mortality,underscoring the urgent need for intelligent diagnostic tools to enhance early detection,prediction,diagnosis,prevention,treatment,and recovery.This demand has spurred the advancement of wearable and flexible technologies,revolutionizing continuous,noninvasive,and remote heart sound(HS)monitoring—a vital avenue for assessing heart activity.The conventional stethoscope,used to listen to HSs,has limitations in terms of its physical structure,as it is inflexible and bulky,which restricts its prospective applications.Recently,mechanoacoustic sensors have made remarkable advancements,evolving from primitive forms to soft,flexible,and wearable designs.This article provides an in-depth review of the latest scientific and technological advancements by addressing various topics,including different types of sensors,sensing materials,design principles,denoising techniques,and clinical applications of flexible and wearable HS sensors.This transformative potential lies in the capacity for ongoing,remote,and personalized monitoring,promising enhanced patient outcomes,amplified remote monitoring capabilities,and timely diagnoses.Last,the article highlights current challenges and prospects for the future,suggesting techniques to advance HS sensing technologies for exciting real‐time applications.
基金financially supported by National Natural Science Foundation of China(Nos.U2001215,52272175,12104517)Natural Science Foundation of Guangdong Province(Nos.2022A1515011487,2021A1515110403)+1 种基金Young Top Talents Program(No.2021QN02C068)State Key Laboratory of Optoelectronic Materials and Technologies(Sun Yat-sen University).
文摘Wearable photodetectors have come under the limelight of optoelectronic technologies on account of multiple advantages spanning light weight,easy-portability,excellent bendability,outstanding conformability,etc.Among diverse candidate materials,low-dimensional van der Waals materials(LDvdWMs)have emerged to be preeminent owing to the dangling-bond-free surface,exceptional carrier mobility,nanoscale dimensionality,and excellent light-harvesting capability.However,to date,the majority of flexible LDvdWM photodetectors have been fabricated through exfoliation-,transfer-,or solution-processing methods,which are plagued by limitations such as low production yield,inadequate photosensitivity,and sluggish response rate.Thus far,constructing LDvdWM photodetectors in situ on flexible substrates remains quite challenging due to the irreconcilable contradiction between the weak robustness of flexible polymer substrates against high temperature and the large thermal budget required for crystallization.This study develops scalable preparation of Sb_(2)Se_(3)nanofilm directly on flexible polyimide substrates by exploiting pulsed-laser deposition(PLD),where highly energetic species can be generated to enable overcoming the reaction barrier for crystallization at a relatively low temperature.The corresponding Sb_(2)Se_(3)photodetectors have exhibited high responsivity of 1.15 A/W,exceptional external quantum efficiency of 269%,and impressive specific detectivity reaching 2.4×10^(11)Jones,coupled with swift switching characteristics.Importantly,excellent durability to repeated bending treatments has been confirmed by the consistent photoresponse over 500 convex/concave bending cycles.Furthermore,the device has showcased strong robustness against extrinsic impinging.In the end,by using Sb_(2)Se_(3)photodetectors as sensing components,wide-band imaging beyond human vision and heart rate monitoring have been realized.This study has underscored the high efficacy of PLD for reconciling the long-standing contradiction between the weak robustness of flexible polymer substrates against high temperature and the substantial thermal energy required for crystallization,opening new opportunities towards next-generation wearable optoelectronic industry.
文摘With the increasing aging population and personalized health management needs,this paper proposes an IoT-based home heart rate monitoring system.The system uses the STM32 microcontroller as the core,integrating a PPG sensor and a body temperature sensor to collect physiological data such as heart rate,blood oxygen saturation,and body temperature.The data is transmitted in real-time to the server and mobile application via the ESP8266 module.Users can view historical data,set alarm thresholds,and re ceive alerts through sound alarms and push notifications when abnormalities are detected.The test results show that the heart rate measurement error is less than 5%,verifying the practicality and reliability of the system in home healt h monitoring and ch ronic disease prevention.This research provides a cost-effective solution for home users who require convenient and continuous health monitoring,especially for the elderly and patients with chronic diseases.
文摘A low power wavelet denoising chip for photoplethysmography （PPG） detection and portable heart rate monitoring is presented. To eliminate noise and improve detection accuracy, Harr wavelet （HWT） is chosen as the processing tool. An optimized finite impulse response structure is proposed to lower the computational complexity of proposed algorithm, which is benefit for reducing the power consumption of proposed chip. The modulus max- ima pair location module is design to accurately locate the PPG peaks. A clock control unit is designed to further reduce the power consumption of the proposed chip. Fabricated with the 0.18μm N-well CMOS 1P6M technol- ogy, the power consumption of proposed chip is only 8.12μW in 1 V voltage supply. Validated with PPG signals in multiparameter intelligent monitoring in intensive care databases and signals acquired by the wrist photoelectric volume detection front end, the proposed chip can accurately detect PPG signals. The average sensitivity and positive prediction are 99.91% and 100%, respectively.
基金supported by the Directorate of Research and Community Service-Ministry of ResearchTechnology and Higher Education,Republic of Indonesia(Grant Nos.6/E/KPT/2019 and 954/PKS/ITS/2019).
文摘The singlemode-multimode-singlemode(SMS)fiber structure for a heart rate monitoring is proposed and developed.An artificial electrocardiogram(ECG)signal is used to simulate the heart pulse at different rates ranging from 50 beats per minute(bpm)to 200 bpm.The SMS fiber structure is placed at the center of a loudspeaker and it senses the vibration of the pulse.The vibration of the pulse signal applied to the SMS fiber structure changes the intensity of the optical output power.The proposed sensor shows a linear frequency of the heart rate sensing range that matches well with the relevant heart rate from the artificial ECG.This work shows the capability of the SMS fiber structure monitoring the heart rate frequencies for a long term,high stability realization,and reproducibility,and being suitable for the observation in hospitals as well as in other environments.
文摘Fatigue impairs workers’judgment,reduces their productivity,and jeopardizes their safety.The paper presents a tool to predict workers’fatigue based on their vital signs.An experimental study was conducted in which the heart rate and sleep quality for three individuals were monitored using fitness trackers(wearable sensors).The data collected were used to develop two models based on regression analysis and Artificial Neural Networks(ANN),to predict their fatigue level.A Borg’s scale was used to estimate the Rating of Perceived Exertion(RPE)of the participants.The two models were able to satisfactorily predict the RPE(workers fatigue level)with an average validity of 75%and 80%for the regression ANN models,respectively.The developed models can provide project managers and superintendents with early warning to avoid potential worker overexertion,injuries,and fatalities.
基金partially supported by the Ministry of Science and Technology of the People's Republic of China with the STI2030-Major Projects(2021ZD0201900)the National Natural Science Foundation of China(No.62227807 and 62272044)+3 种基金the Teli Young Fellow Program from the Beijing Institute of Technology,Chinathe Natural Science Foundation of Shenzhen University General Hospital(No.SUGH2018QD013),Chinathe Shenzhen Science and Technology Innovation Commission Project(No.JCYJ20190808120613189),Chinathe Grants-in-Aid for Scientific Research(No.20H00569)from the Ministry of Education,Culture,Sports,Science and Technology(MEXT),Japan.
文摘Leveraging the power of artificial intelligence to facilitate an automatic analysis and monitoring of heart sounds has increasingly attracted tremendous efforts in the past decade.Nevertheless,lacking on standard open-access database made it difficult to maintain a sustainable and comparable research before the first release of the PhysioNet CinC Challenge Dataset.However,inconsistent standards on data collection,annotation,and partition are still restraining a fair and efficient comparison between different works.To this line,we introduced and benchmarked a first version of the Heart Sounds Shenzhen(HSS)corpus.Motivated and inspired by the previous works based on HSS,we redefined the tasks and make a comprehensive investigation on shallow and deep models in this study.First,we segmented the heart sound recording into shorter recordings(10 s),which makes it more similar to the human auscultation case.Second,we redefined the classification tasks.Besides using the 3 class categories(normal,moderate,and mild/severe)adopted in HSS,we added a binary classification task in this study,i.e.,normal and abnormal.In this work,we provided detailed benchmarks based on both the classic machine learning and the state-of-the-art deep learning technologies,which are reproducible by using open-source toolkits.Last but not least,we analyzed the feature contributions of best performance achieved by the benchmark to make the results more convincing and interpretable.
文摘During surgery,a heartbeat doesn’t just tell whether a person is dead or alive-it can warn of big problems that come up quite suddenly.Keeping watch for subtle irregularities in the heart’s electric activity can help save a patient’s life.But today’s technology can’t give as much detail as doctors
