V. Osmani, S. Forti, O. Mayora-Ibarra, D. Conforti
We describe an innovative framework for prescription of personalised health apps by integrating Personal Health Records (PHR) with disease-specific mobile applications for managing medical conditions and the communication with clinical professionals. The prescribed apps record multiple variables including medical history enriched with innovative features such as integration with medical monitoring devices and wellbeing trackers to provide patients and clinicians with a personalised support on disease management. Our framework is based on an existing PHR ecosystem called TreC, uniquely positioned between healthcare provider and the patients, which is being used by over 70.000 patients in Trentino region in Northern Italy. We also describe three important aspects of health app prescription and how medical information is automatically encoded through the TreC framework and is prescribed as a personalised app, ready to be installed in the patients' smartphone.
{"title":"Enabling prescription-based health apps","authors":"V. Osmani, S. Forti, O. Mayora-Ibarra, D. Conforti","doi":"10.1145/3154862.3154911","DOIUrl":"https://doi.org/10.1145/3154862.3154911","url":null,"abstract":"We describe an innovative framework for prescription of personalised health apps by integrating Personal Health Records (PHR) with disease-specific mobile applications for managing medical conditions and the communication with clinical professionals. The prescribed apps record multiple variables including medical history enriched with innovative features such as integration with medical monitoring devices and wellbeing trackers to provide patients and clinicians with a personalised support on disease management. Our framework is based on an existing PHR ecosystem called TreC, uniquely positioned between healthcare provider and the patients, which is being used by over 70.000 patients in Trentino region in Northern Italy. We also describe three important aspects of health app prescription and how medical information is automatically encoded through the TreC framework and is prescribed as a personalised app, ready to be installed in the patients' smartphone.","PeriodicalId":200810,"journal":{"name":"Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125296690","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}
Hariharan Subramonyam, Bongshin Lee, M. S. O'Modhrain, Eytan Adar
Shared decision-making is a process that requires active participation from the patient in making treatment related decisions [5]. Through this process, both patients and clinicians develop a shared understanding about the patients' lifestyle choices and how they affect symptoms to make informed treatment related decisions. However, there are communication and process barriers to developing this understanding, including lack of medical knowledge on the part of the patients and lack of standard processes for clinicians to follow. With Data Dialog, we propose a data-driven approach to information exchange between patients and clinicians, using visualizations as 'boundary objects' for communication and collaboration. We outline a number of scenarios in which Data Dialog can be useful, and discuss opportunities and challenges that need to be addressed.
{"title":"Data dialog: facilitating collaborative decision making through data-driven conversations","authors":"Hariharan Subramonyam, Bongshin Lee, M. S. O'Modhrain, Eytan Adar","doi":"10.1145/3154862.3154921","DOIUrl":"https://doi.org/10.1145/3154862.3154921","url":null,"abstract":"Shared decision-making is a process that requires active participation from the patient in making treatment related decisions [5]. Through this process, both patients and clinicians develop a shared understanding about the patients' lifestyle choices and how they affect symptoms to make informed treatment related decisions. However, there are communication and process barriers to developing this understanding, including lack of medical knowledge on the part of the patients and lack of standard processes for clinicians to follow. With Data Dialog, we propose a data-driven approach to information exchange between patients and clinicians, using visualizations as 'boundary objects' for communication and collaboration. We outline a number of scenarios in which Data Dialog can be useful, and discuss opportunities and challenges that need to be addressed.","PeriodicalId":200810,"journal":{"name":"Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123720319","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}
Carme Zambrana, Sebastian Idelsohn-Zielonka, Mireia Claramunt-Molet, Maria Almenara-Masbernat, E. Opisso, J. Tormos, F. Miralles, E. Vargiu
One of the most relevant post-stroke conditions is the hemiparesis, which causes muscle weakness and/or the inability to move one side of the body. Physical and occupational therapy plays an important role in the rehabilitation of patients suffering this condition. On the other hand, daily life use of the impaired arm is crucial for improving and also assessing the evolution of the patient. Currently, this assessment is done through self-questionnaires and interviews, which are subjective and depend on the memory of the patient. In this paper, a hierarchical automatic approach aimed at recognizing purposeful arm movements during patients' daily life activities is presented. This approach relies on two-levels: the former is aimed at distinguishing between arm movement and non-movement; whereas the latter is devoted to recognize between purposeful and non-purposeful movements. In particular, in the first version of the system, we consider arms swing while walking as non-purposeful movement. Experiments have been performed in the lab with 9 healthy volunteers wearing a wristband on each wrist. Six activities have been performed: eating, pouring water, drinking, brushing their teeth, folding a towel, and walking. The proposed approach achieves promising performances, recognizing purposeful movement with an accuracy of 0.91 and an F1-score of 0.87.
{"title":"A hierarchical approach to recognize purposeful movements using inertial sensors: preliminary experiments and results","authors":"Carme Zambrana, Sebastian Idelsohn-Zielonka, Mireia Claramunt-Molet, Maria Almenara-Masbernat, E. Opisso, J. Tormos, F. Miralles, E. Vargiu","doi":"10.1145/3154862.3154932","DOIUrl":"https://doi.org/10.1145/3154862.3154932","url":null,"abstract":"One of the most relevant post-stroke conditions is the hemiparesis, which causes muscle weakness and/or the inability to move one side of the body. Physical and occupational therapy plays an important role in the rehabilitation of patients suffering this condition. On the other hand, daily life use of the impaired arm is crucial for improving and also assessing the evolution of the patient. Currently, this assessment is done through self-questionnaires and interviews, which are subjective and depend on the memory of the patient. In this paper, a hierarchical automatic approach aimed at recognizing purposeful arm movements during patients' daily life activities is presented. This approach relies on two-levels: the former is aimed at distinguishing between arm movement and non-movement; whereas the latter is devoted to recognize between purposeful and non-purposeful movements. In particular, in the first version of the system, we consider arms swing while walking as non-purposeful movement. Experiments have been performed in the lab with 9 healthy volunteers wearing a wristband on each wrist. Six activities have been performed: eating, pouring water, drinking, brushing their teeth, folding a towel, and walking. The proposed approach achieves promising performances, recognizing purposeful movement with an accuracy of 0.91 and an F1-score of 0.87.","PeriodicalId":200810,"journal":{"name":"Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125844888","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}
T. Andersen, Pernille R. D. Andersen, Anders C. Kornum, Trine M. Larsen
The term 'patient experience' is currently part of a global discourse on ways to improve healthcare. This study empirically explores what patient experience is in cardiac remote monitoring and considers the implications for user experience (UX). Through interviews around the deployment of a mobile app that enables patients to collaborate with clinicians, we unpack experiences in six themes and present narratives of patients' lifeworlds. We find that patients' emotions are grounded in negative feelings (uncertainty, anxiety, loss of hope) and that positive experiences (relief, reassurance, safety) arise from getting feedback on symptoms and from continuous and comforting interaction with clinicians. With this paper, we aim to sensitise UX researchers and designers of patient-centred e-health by proposing three UX dimensions: connectedness, comprehension, and compassion.
{"title":"Understanding patient experience: a deployment study in cardiac remote monitoring","authors":"T. Andersen, Pernille R. D. Andersen, Anders C. Kornum, Trine M. Larsen","doi":"10.1145/3154862.3154868","DOIUrl":"https://doi.org/10.1145/3154862.3154868","url":null,"abstract":"The term 'patient experience' is currently part of a global discourse on ways to improve healthcare. This study empirically explores what patient experience is in cardiac remote monitoring and considers the implications for user experience (UX). Through interviews around the deployment of a mobile app that enables patients to collaborate with clinicians, we unpack experiences in six themes and present narratives of patients' lifeworlds. We find that patients' emotions are grounded in negative feelings (uncertainty, anxiety, loss of hope) and that positive experiences (relief, reassurance, safety) arise from getting feedback on symptoms and from continuous and comforting interaction with clinicians. With this paper, we aim to sensitise UX researchers and designers of patient-centred e-health by proposing three UX dimensions: connectedness, comprehension, and compassion.","PeriodicalId":200810,"journal":{"name":"Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121972951","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}
V. Ramesh, K. Agrawal, B. Meyer, G. Cauwenberghs, Nadir Weibel
Hemiparesis, the weakness of one side of the body, affects the ability of stroke survivors to move and walk. With prevalence in 80% of survivors, hemiparesis is an important measure for stroke severity. It is generally diagnosed through motor tests performed as part of the National Institute of Health Stroke Scale (NIHSS). Here we report on initial work for an alternate way of identifying hemiparesis that leverages body joint position data captured by the Microsoft Kinect v2 of people resting while waiting for the neurological examination. We employ support vector machines with 10 stroke patients and 9 healthy controls to characterize hemiparesis based on the lower core body angles of the participants, and compare our results to neurologists' diagnoses. We were able to identify left-side hemiparesis, right-side hemiparesis, or no hemiparesis with > 89% accuracy when looking at the lower body angles and observing the patients for 1 minute.
{"title":"Exploring stroke-associated hemiparesis assessment with support vector machines","authors":"V. Ramesh, K. Agrawal, B. Meyer, G. Cauwenberghs, Nadir Weibel","doi":"10.1145/3154862.3154894","DOIUrl":"https://doi.org/10.1145/3154862.3154894","url":null,"abstract":"Hemiparesis, the weakness of one side of the body, affects the ability of stroke survivors to move and walk. With prevalence in 80% of survivors, hemiparesis is an important measure for stroke severity. It is generally diagnosed through motor tests performed as part of the National Institute of Health Stroke Scale (NIHSS). Here we report on initial work for an alternate way of identifying hemiparesis that leverages body joint position data captured by the Microsoft Kinect v2 of people resting while waiting for the neurological examination. We employ support vector machines with 10 stroke patients and 9 healthy controls to characterize hemiparesis based on the lower core body angles of the participants, and compare our results to neurologists' diagnoses. We were able to identify left-side hemiparesis, right-side hemiparesis, or no hemiparesis with > 89% accuracy when looking at the lower body angles and observing the patients for 1 minute.","PeriodicalId":200810,"journal":{"name":"Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128182668","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}
F. Rajabiyazdi, Charles Perin, L. Oehlberg, M. Carpendale
While patients' increasing willingness to collect personal health data portends improvements in the individualization of health care, helping health care providers to effectively act upon these personal data collections poses its own challenges. In this paper, we discuss the challenges we have noticed as we work towards the creation of tools to help chronic patients present their data to their clinicians.
{"title":"The challenges of individuality to technology approaches to personally collected health data","authors":"F. Rajabiyazdi, Charles Perin, L. Oehlberg, M. Carpendale","doi":"10.1145/3154862.3154923","DOIUrl":"https://doi.org/10.1145/3154862.3154923","url":null,"abstract":"While patients' increasing willingness to collect personal health data portends improvements in the individualization of health care, helping health care providers to effectively act upon these personal data collections poses its own challenges. In this paper, we discuss the challenges we have noticed as we work towards the creation of tools to help chronic patients present their data to their clinicians.","PeriodicalId":200810,"journal":{"name":"Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123205247","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 ability to share automatically tracked health and fitness behaviors has yielded benefits ranging from increasing user motivation to providing therapists with greater insight into their patients' progress. While past work on sharing this data has primarily focused on users with typical motor abilities, features are now emerging in mainstream tracking technologies to extend to people with mobility impairments (e.g., tracking wheelchair rolling). This paper explores opportunities specifically for users with mobility impairments to share this automatically tracked data both with peers and with physical, occupational or recreational therapists. We conducted semi-structured interviews with 10 therapists and 10 people with mobility impairments. The interviews focused on current and desired activity-tracking and sharing practices, and included a design probe activity to more concretely assess the perceived utility of sharing tracked fitness data. We report on attitudes and concerns toward sharing fitness data from the perspective of therapists and people with mobility impairments as well as outline design opportunities to explore in future work.
{"title":"Sharing automatically tracked activity data: implications for therapists and people with mobility impairments","authors":"Meethu Malu, Leah Findlater","doi":"10.1145/3154862.3154864","DOIUrl":"https://doi.org/10.1145/3154862.3154864","url":null,"abstract":"The ability to share automatically tracked health and fitness behaviors has yielded benefits ranging from increasing user motivation to providing therapists with greater insight into their patients' progress. While past work on sharing this data has primarily focused on users with typical motor abilities, features are now emerging in mainstream tracking technologies to extend to people with mobility impairments (e.g., tracking wheelchair rolling). This paper explores opportunities specifically for users with mobility impairments to share this automatically tracked data both with peers and with physical, occupational or recreational therapists. We conducted semi-structured interviews with 10 therapists and 10 people with mobility impairments. The interviews focused on current and desired activity-tracking and sharing practices, and included a design probe activity to more concretely assess the perceived utility of sharing tracked fitness data. We report on attitudes and concerns toward sharing fitness data from the perspective of therapists and people with mobility impairments as well as outline design opportunities to explore in future work.","PeriodicalId":200810,"journal":{"name":"Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122084861","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}
A longitudinal study in the home setting using inexpensive depth cameras was done over 34 months to investigate the ability to predict clinical events. Previous work developed a set of metrics based upon the movement of the centroid computed from segmented depth data [14]. A predictive analysis method is developed allowing the identification of significant changes in the subject's gait. These changes are compared to the subject's clinical events and correlated with standard Fall Risk Assessments (FRA). The method developed here allows the proper clustering of all purposeful walks in the residence to isolate the subject from visitors, and identification of significant changes using a set of metrics unique to each subject. Correct detection of events and non-events ranged between 75% and 94% across a set of 7 residents. These predicted events were also found to correlate strongly with established monthly FRAs.
{"title":"Exploring clinical correlations in centroid-based gait metrics from depth data collected in the home","authors":"Robert Wallace, C. Abbott, M. Skubic","doi":"10.1145/3154862.3154890","DOIUrl":"https://doi.org/10.1145/3154862.3154890","url":null,"abstract":"A longitudinal study in the home setting using inexpensive depth cameras was done over 34 months to investigate the ability to predict clinical events. Previous work developed a set of metrics based upon the movement of the centroid computed from segmented depth data [14]. A predictive analysis method is developed allowing the identification of significant changes in the subject's gait. These changes are compared to the subject's clinical events and correlated with standard Fall Risk Assessments (FRA). The method developed here allows the proper clustering of all purposeful walks in the residence to isolate the subject from visitors, and identification of significant changes using a set of metrics unique to each subject. Correct detection of events and non-events ranged between 75% and 94% across a set of 7 residents. These predicted events were also found to correlate strongly with established monthly FRAs.","PeriodicalId":200810,"journal":{"name":"Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127033121","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}
This research examines how wearable technology and supporting applications can help office workers maintain good posture and guide them to carry out shoulder exercises at their workplace. Specifically, we describe a smart garment designed to monitor upper body posture that provides vibrotactile notifications at different joint areas in order to remind users to correct their posture. We present the design and evaluation of a related smartphone application that supports shoulder training exercises to treat and prevent shoulder pain. The usability of the system for shoulder training was evaluated positively in a laboratory test (N=17). The effectiveness of the system for posture monitoring was assessed with a field deployment (N=25) in which students working with laptops used the posture monitoring system for a whole day. The results demonstrate the system can help the participants facilitate improving their posture in sedentary work.
{"title":"Supporting shoulder pain prevention and treatment with wearable technology","authors":"Jiachun Du, Qi Wang, L. D. Baets, P. Markopoulos","doi":"10.1145/3154862.3154886","DOIUrl":"https://doi.org/10.1145/3154862.3154886","url":null,"abstract":"This research examines how wearable technology and supporting applications can help office workers maintain good posture and guide them to carry out shoulder exercises at their workplace. Specifically, we describe a smart garment designed to monitor upper body posture that provides vibrotactile notifications at different joint areas in order to remind users to correct their posture. We present the design and evaluation of a related smartphone application that supports shoulder training exercises to treat and prevent shoulder pain. The usability of the system for shoulder training was evaluated positively in a laboratory test (N=17). The effectiveness of the system for posture monitoring was assessed with a field deployment (N=25) in which students working with laptops used the posture monitoring system for a whole day. The results demonstrate the system can help the participants facilitate improving their posture in sedentary work.","PeriodicalId":200810,"journal":{"name":"Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131056986","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}
Dawood Al-Masslawi, Lori Block, C. Ronquillo, Shannon Handfield, S. Fels, R. Lea, L. Currie
The increasing aging population needing homecare is leading to additional clinical work for homecare nurses. Wound care and documentation are substantial components of this work required to monitor patients and make appropriate clinical decisions. However, due to barriers in the systems that nurses are expected to use, and context of their activities, they create and use workarounds to get their job done. In this study, the most common themes of workarounds were identified and used to inform design iterations of a wound documentation application: SuperNurse. The exploratory and experimental design iterations involved homecare nurses, who expressed: curiosity, leading to further reflection; frustration, leading to identifying problems; and surprise, leading to identifying useful and easy to use designs. We found that nurse-centred design, informed by workarounds, led to using mobile, wearable, and speech recognition technology and improving ease of use and usefulness in SuperNurse.
{"title":"SuperNurse: nurses' workarounds informing the design of interactive technologies for home wound care","authors":"Dawood Al-Masslawi, Lori Block, C. Ronquillo, Shannon Handfield, S. Fels, R. Lea, L. Currie","doi":"10.1145/3154862.3154865","DOIUrl":"https://doi.org/10.1145/3154862.3154865","url":null,"abstract":"The increasing aging population needing homecare is leading to additional clinical work for homecare nurses. Wound care and documentation are substantial components of this work required to monitor patients and make appropriate clinical decisions. However, due to barriers in the systems that nurses are expected to use, and context of their activities, they create and use workarounds to get their job done. In this study, the most common themes of workarounds were identified and used to inform design iterations of a wound documentation application: SuperNurse. The exploratory and experimental design iterations involved homecare nurses, who expressed: curiosity, leading to further reflection; frustration, leading to identifying problems; and surprise, leading to identifying useful and easy to use designs. We found that nurse-centred design, informed by workarounds, led to using mobile, wearable, and speech recognition technology and improving ease of use and usefulness in SuperNurse.","PeriodicalId":200810,"journal":{"name":"Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123232729","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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