Reliable sensor operation is a must for health care cyber-biological systems, such as closed-loop glucose control. In this paper, we outline the scheme for fault tolerant measurements, re-calibration and the replacement of permanently failed sensors.
{"title":"Fault tolerant glucose sensor readout and recalibration","authors":"Z. Zilic, K. Radecka","doi":"10.1145/2077546.2077585","DOIUrl":"https://doi.org/10.1145/2077546.2077585","url":null,"abstract":"Reliable sensor operation is a must for health care cyber-biological systems, such as closed-loop glucose control. In this paper, we outline the scheme for fault tolerant measurements, re-calibration and the replacement of permanently failed sensors.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"19 1","pages":"35"},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74547267","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}
Hidden Markov Model (HMM) is a well established technique for detecting patterns in a stream of observations. It performs well when the observation sequence does not contain unseen patterns that were not part of the training set. In an unconstrained environment, the observation sequence might contain new patterns that the HMM model is not familiar with. In such cases, HMM will match the test pattern to some trained pattern, which is most similar to the test pattern. This increases the false positives in the system. In this paper, we are describing a threshold based technique to detect such irrelevant patterns in a continuous stream of observations, and classify them as unwanted or bad patterns. The novelty of our approach is that it allows early detection of unwanted patterns. Test patterns are validated on a fixed length substring of observation sequence, rather than on the whole observation sequence corresponding to the test pattern. The substrings are validated based on its similarity with a valid pattern using a threshold value. This reduces the latency of detection of unwanted movement, and makes the detection process independent of duration of the various pattern classes. We evaluated this technique in the context of body sensor networks based human action recognition, and have achieved about 93 percent accuracy in detecting unwanted actions, while maintaining a 94 percent accuracy of recognizing valid actions.
{"title":"Rejection of irrelevant human actions in real-time hidden Markov model based recognition systems for wearable computers","authors":"Jerry Mannil, Mohammad-Mahdi Bidmeshki, R. Jafari","doi":"10.1145/2077546.2077555","DOIUrl":"https://doi.org/10.1145/2077546.2077555","url":null,"abstract":"Hidden Markov Model (HMM) is a well established technique for detecting patterns in a stream of observations. It performs well when the observation sequence does not contain unseen patterns that were not part of the training set. In an unconstrained environment, the observation sequence might contain new patterns that the HMM model is not familiar with. In such cases, HMM will match the test pattern to some trained pattern, which is most similar to the test pattern. This increases the false positives in the system. In this paper, we are describing a threshold based technique to detect such irrelevant patterns in a continuous stream of observations, and classify them as unwanted or bad patterns. The novelty of our approach is that it allows early detection of unwanted patterns. Test patterns are validated on a fixed length substring of observation sequence, rather than on the whole observation sequence corresponding to the test pattern. The substrings are validated based on its similarity with a valid pattern using a threshold value. This reduces the latency of detection of unwanted movement, and makes the detection process independent of duration of the various pattern classes. We evaluated this technique in the context of body sensor networks based human action recognition, and have achieved about 93 percent accuracy in detecting unwanted actions, while maintaining a 94 percent accuracy of recognizing valid actions.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87161307","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}
Frank Wang, Yeung Lam, A. Mehrnia, B. Bates-Jensen, M. Sarrafzadeh, W. Kaiser
Pressure Ulcer (PU) incidence leads to considerable risk, in particular for the frail elderly, and a large national healthcare treatment cost. Evidence-based methods for assuring the health and safety of patients are urgently needed. Recent clinical trials have demonstrated that sub-epidermal moisture (SEM) present in tissue may be measured by interrogation of tissue dielectric properties and are associated with the presence of erythema and development of early stage PU conditions. A novel wireless handheld device has been developed and will be demonstrated that introduces a series of advances including automated measurement, automated measurement method assurance including application of proper measurement applied pressure, and wireless energy recharge capability. This advances previous successful prototype development to now include a complete point-of-care usage product. This device, termed the SEM Scanner, was successfully verified in trials with 30 subjects and is currently deployed in large clinical trials in nursing homes in Los Angeles. This manuscript and the planned demonstration describe a set of significant technology advances over previous technology based on both new Wireless Health hardware and software system solutions. In addition to the demonstration to be provided of a novel end-to-end system including data acquisition, data archiving, reporting, and compliance verification, data from trials will also be presented.
{"title":"A wireless biomedical handheld instrument for evidence-based detection of pressure ulcers","authors":"Frank Wang, Yeung Lam, A. Mehrnia, B. Bates-Jensen, M. Sarrafzadeh, W. Kaiser","doi":"10.1145/2077546.2077582","DOIUrl":"https://doi.org/10.1145/2077546.2077582","url":null,"abstract":"Pressure Ulcer (PU) incidence leads to considerable risk, in particular for the frail elderly, and a large national healthcare treatment cost. Evidence-based methods for assuring the health and safety of patients are urgently needed. Recent clinical trials have demonstrated that sub-epidermal moisture (SEM) present in tissue may be measured by interrogation of tissue dielectric properties and are associated with the presence of erythema and development of early stage PU conditions. A novel wireless handheld device has been developed and will be demonstrated that introduces a series of advances including automated measurement, automated measurement method assurance including application of proper measurement applied pressure, and wireless energy recharge capability. This advances previous successful prototype development to now include a complete point-of-care usage product. This device, termed the SEM Scanner, was successfully verified in trials with 30 subjects and is currently deployed in large clinical trials in nursing homes in Los Angeles. This manuscript and the planned demonstration describe a set of significant technology advances over previous technology based on both new Wireless Health hardware and software system solutions. In addition to the demonstration to be provided of a novel end-to-end system including data acquisition, data archiving, reporting, and compliance verification, data from trials will also be presented.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"5 1","pages":"33"},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88821730","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}
We present a multi-modal emotion recognition system for persistent and non-invasive personal health monitoring. Our system is capable of effectively estimating human emotional states through analyzing and fusing a number of non-invasive external cues (such as facial expression, body posture, and voice intonation) in a systematic way through utilizing a probabilistic information fusion model.
{"title":"A multi-modal emotion recognition system for persistent and non-invasive personal health monitoring","authors":"Xiaoqing Liu, Lei Zhang, J. Yadegar","doi":"10.1145/2077546.2077577","DOIUrl":"https://doi.org/10.1145/2077546.2077577","url":null,"abstract":"We present a multi-modal emotion recognition system for persistent and non-invasive personal health monitoring. Our system is capable of effectively estimating human emotional states through analyzing and fusing a number of non-invasive external cues (such as facial expression, body posture, and voice intonation) in a systematic way through utilizing a probabilistic information fusion model.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"2 1","pages":"28"},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79204026","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}
In this proposal, we describe the technology of Wireless Health Interactive, LLC (BeClose.com) and demonstrate the capabilities of the BeClose platform for in home assessment of health and wellness to promote aging-in-place. We describe recent efforts to incorporate ambient, artificial intelligence to contextualize data for recognition of activities of daily living. Finally, we illustrate the potential of the technology regarding the aged demographic -- as a tool to manage independent living with dementia. This work will showcase recent innovations in the development and commercialization of wireless health products and provide outcome-oriented use cases derived from ongoing research.
{"title":"In home assessment and management of health and wellness with BeClose#8482; ambient, artificial intelligence","authors":"M. Hanson, Adam T. Barth, Christopher Silverman","doi":"10.1145/2077546.2077574","DOIUrl":"https://doi.org/10.1145/2077546.2077574","url":null,"abstract":"In this proposal, we describe the technology of Wireless Health Interactive, LLC (BeClose.com) and demonstrate the capabilities of the BeClose platform for in home assessment of health and wellness to promote aging-in-place. We describe recent efforts to incorporate ambient, artificial intelligence to contextualize data for recognition of activities of daily living. Finally, we illustrate the potential of the technology regarding the aged demographic -- as a tool to manage independent living with dementia. This work will showcase recent innovations in the development and commercialization of wireless health products and provide outcome-oriented use cases derived from ongoing research.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"25 1","pages":"25"},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76774046","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}
The causes of stress and how it affects our behaviors are generally not well understood. The stress research usually requires a large amount of data to analyze possible stress-related factors. The data collection process traditionally is time-consuming and cost-ineffective. To help medical researchers collect the stress information, we propose a tool named StressBar utilizing the powerful data collection capacity of smart phones. In this paper, we will show our design and implementation considerations of StressBar.
{"title":"StressBar: a system for stress information collection","authors":"Dajun Lu, Guoxing Zhan, Shinan Wang, Weisong Shi, Clairy Wiholm, B. Arnetz","doi":"10.1145/2077546.2077578","DOIUrl":"https://doi.org/10.1145/2077546.2077578","url":null,"abstract":"The causes of stress and how it affects our behaviors are generally not well understood. The stress research usually requires a large amount of data to analyze possible stress-related factors. The data collection process traditionally is time-consuming and cost-ineffective. To help medical researchers collect the stress information, we propose a tool named StressBar utilizing the powerful data collection capacity of smart phones. In this paper, we will show our design and implementation considerations of StressBar.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"49 1","pages":"29"},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83729961","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}
Zainul Charbiwala, J. Friedman, M. Srivastava, B. Kuris
With recent improvements in the energy efficiency of digital microprocessors and radio transceivers, the relative contribution of the analog front end in the overall power consumption of a wireless health system has been steadily rising. A key reason for this is that sampling rates in most medical applications are extremely low, providing opportunities to aggressively duty cycle the power hungry processor and radio. Analog front ends have not traditionally been duty cycled because analog filters with large time constants dictate a prohibitively high wake up latency. In this paper, we show that this latency can be reduced to a large extent and duty cycling made feasible by making filters "remember" their state across power gating cycles. This is done using slight hardware modifications that can even be applied to existing boards. We illustrate our technique on a commercially available wireless electro-cardiography system. Using our methodology, we reduced the restart delay of the circuit by three orders of magnitude from 6s to 5ms. We employ our circuit design for energy efficient QRS complex detection and extraction, which results in a 3× reduction in analog front end energy consumption.
{"title":"Filters that remember: duty cycling analog circuits for long term medical monitoring","authors":"Zainul Charbiwala, J. Friedman, M. Srivastava, B. Kuris","doi":"10.1145/2077546.2077550","DOIUrl":"https://doi.org/10.1145/2077546.2077550","url":null,"abstract":"With recent improvements in the energy efficiency of digital microprocessors and radio transceivers, the relative contribution of the analog front end in the overall power consumption of a wireless health system has been steadily rising. A key reason for this is that sampling rates in most medical applications are extremely low, providing opportunities to aggressively duty cycle the power hungry processor and radio. Analog front ends have not traditionally been duty cycled because analog filters with large time constants dictate a prohibitively high wake up latency. In this paper, we show that this latency can be reduced to a large extent and duty cycling made feasible by making filters \"remember\" their state across power gating cycles. This is done using slight hardware modifications that can even be applied to existing boards. We illustrate our technique on a commercially available wireless electro-cardiography system. Using our methodology, we reduced the restart delay of the circuit by three orders of magnitude from 6s to 5ms. We employ our circuit design for energy efficient QRS complex detection and extraction, which results in a 3× reduction in analog front end energy consumption.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"325 1","pages":"3"},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91429766","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}
In this demo, we present PAMSys#8482;(physical activity monitoring system), a single body sensor solution for long-term and continuous monitoring of a person's daily activities. PAMSys#8482; requires only a single light-weight sensor unit that can be integrated unobtrusively into a comfortable shirt (or directly to a subject's shirt) without hindering daily-living activities. The use of large flash storage and low power sensor technologies allows a maximal system lifetime of 8 days on a single charge, minimizing the management burden of the users of the system. PAMWare#8482;, the data analysis software for PAMSys#8482;, performs advanced biomechanical analyses on the tri-axial accelerometer signals recorded by the sensor unit and generates a detailed report on the subject's postural information throughout the entire measurement period. The system can be used for monitoring the state of health in the elderly, as well as the effect of different medical and surgical procedures in enhancing a patients' quality of life. As an example, long-term physical activity data can be applied to assess the risk of fall for elderly people by monitoring durations of sit-to-stand posture transitions.
{"title":"PAMSys: long-term physical activity monitoring with single wearable motion sensor","authors":"Bor-rong Chen, Bryan Kate","doi":"10.1145/2077546.2077570","DOIUrl":"https://doi.org/10.1145/2077546.2077570","url":null,"abstract":"In this demo, we present PAMSys#8482;(physical activity monitoring system), a single body sensor solution for long-term and continuous monitoring of a person's daily activities. PAMSys#8482; requires only a single light-weight sensor unit that can be integrated unobtrusively into a comfortable shirt (or directly to a subject's shirt) without hindering daily-living activities. The use of large flash storage and low power sensor technologies allows a maximal system lifetime of 8 days on a single charge, minimizing the management burden of the users of the system. PAMWare#8482;, the data analysis software for PAMSys#8482;, performs advanced biomechanical analyses on the tri-axial accelerometer signals recorded by the sensor unit and generates a detailed report on the subject's postural information throughout the entire measurement period. The system can be used for monitoring the state of health in the elderly, as well as the effect of different medical and surgical procedures in enhancing a patients' quality of life. As an example, long-term physical activity data can be applied to assess the risk of fall for elderly people by monitoring durations of sit-to-stand posture transitions.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"76 1","pages":"21"},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86180179","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}
M. Mollazadeh, Elliot Greenwald, M. Schieber, N. Thakor, G. Cauwenberghs
Electrocorticography (ECoG), the recording of electrical signals from the surface of cortex, is widely used for monitoring and analysis of epileptic brain activity. However, current ECoG recording methods require tethering of the patient causing discomfort and impeding his or her mobility. We demonstrate a system for wireless multichannel recording of ECoG activity. The system is comprised of a custom made VLSI neural front end, transceiver modules, battery and a custom software written in LabView for real-time data monitoring and storage. The system offers programmable gain, bandwidth and ADC setting while maintaining low noise performance and drawing less than 6.7mA of current from 3.7V battery. We have validated this system by recording micro-ECoG signal from the dorsal premotor cortex region of a primate performing reach to grasp movements. In our demonstration, we will show the wireless operation of the system, transmitting pre-recorded ECoG signals from primates through a saline solution. We will also show real-time recording of electromyography (EMG) signals from a human subject performing motor movements. Our system offers a new platform for wireless health monitoring system in epilepsy units.
{"title":"A micropower integrated platform for wireless multichannel recording of ECoG activity","authors":"M. Mollazadeh, Elliot Greenwald, M. Schieber, N. Thakor, G. Cauwenberghs","doi":"10.1145/2077546.2077579","DOIUrl":"https://doi.org/10.1145/2077546.2077579","url":null,"abstract":"Electrocorticography (ECoG), the recording of electrical signals from the surface of cortex, is widely used for monitoring and analysis of epileptic brain activity. However, current ECoG recording methods require tethering of the patient causing discomfort and impeding his or her mobility. We demonstrate a system for wireless multichannel recording of ECoG activity. The system is comprised of a custom made VLSI neural front end, transceiver modules, battery and a custom software written in LabView for real-time data monitoring and storage. The system offers programmable gain, bandwidth and ADC setting while maintaining low noise performance and drawing less than 6.7mA of current from 3.7V battery. We have validated this system by recording micro-ECoG signal from the dorsal premotor cortex region of a primate performing reach to grasp movements. In our demonstration, we will show the wireless operation of the system, transmitting pre-recorded ECoG signals from primates through a saline solution. We will also show real-time recording of electromyography (EMG) signals from a human subject performing motor movements. Our system offers a new platform for wireless health monitoring system in epilepsy units.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"20 1","pages":"30"},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87288507","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}
I. Henry, D. Bernstein, Matt J. Banet, Jane Mulligan, S. Moulton, G. Grudic, V. Convertino
Hemorrhagic shock induced by traumatic injury is a leading cause of mortality on the battlefield and in civilian trauma settings. The first hour following injury can be critical to survival, requiring frequent assessment of vital signs and intravascular volume needs. Conventional vital signs, such as heart rate and blood pressure, are generally nonspecific and slow to change until acute blood loss volume nears 25--30% of total blood volume. The lack of specificity associated with these vital signs limits their usefulness in the early detection and monitoring of acute blood loss. In contrast, measurements of cardiac output (CO), stroke volume (SV) and a new parameter termed Cardiovascular Reserve Index (CRI), follow the progression of hemorrhage and response to intravenous fluid therapy. They are superior indicators of blood loss volume and fluid resuscitation needs. We will demonstrate the implementation of all three parameters on a small, noninvasive body-worn device that is wirelessly connected to a central monitoring system.
{"title":"Body-worn, non-invasive sensor for monitoring stroke volume, cardiac output and cardiovascular reserve","authors":"I. Henry, D. Bernstein, Matt J. Banet, Jane Mulligan, S. Moulton, G. Grudic, V. Convertino","doi":"10.1145/2077546.2077575","DOIUrl":"https://doi.org/10.1145/2077546.2077575","url":null,"abstract":"Hemorrhagic shock induced by traumatic injury is a leading cause of mortality on the battlefield and in civilian trauma settings. The first hour following injury can be critical to survival, requiring frequent assessment of vital signs and intravascular volume needs. Conventional vital signs, such as heart rate and blood pressure, are generally nonspecific and slow to change until acute blood loss volume nears 25--30% of total blood volume. The lack of specificity associated with these vital signs limits their usefulness in the early detection and monitoring of acute blood loss. In contrast, measurements of cardiac output (CO), stroke volume (SV) and a new parameter termed Cardiovascular Reserve Index (CRI), follow the progression of hemorrhage and response to intravenous fluid therapy. They are superior indicators of blood loss volume and fluid resuscitation needs. We will demonstrate the implementation of all three parameters on a small, noninvasive body-worn device that is wirelessly connected to a central monitoring system.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"16 1","pages":"26"},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74630020","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：