将语音辅助整合到智能治疗干预中的通用概念

Jens Scheible, Fabian Hofmann, M. Reichert, R. Pryss, Marc Schickler
{"title":"将语音辅助整合到智能治疗干预中的通用概念","authors":"Jens Scheible, Fabian Hofmann, M. Reichert, R. Pryss, Marc Schickler","doi":"10.1109/CBMS55023.2022.00017","DOIUrl":null,"url":null,"abstract":"Therapeutic Interventions (TIs) play an important role in modern medical and psychological treatments, but their integration into the digital world still shows deficits, e.g., in the integration of the auditory interface. Initiatives to integrate this interface into existing Internet- and Mobile-Based Interventions (IMIs) are largely focused on a small group of Voice Assistants (VAs) and their specific capabilities. To mitigate these drawbacks, the presented concept seamlessly integrates arbitrary VAs into the treatment process of TIs. To this end, an architecture - including a discussion of relevant requirements - is presented that, on the one hand, uses VAs as the only point of contact with patients and, on the other hand, provides a comprehensive web-based backend for Healthcare Providers (HCPs). Based on the architecture, a proof-of-concept implementation using Amazon Alexa is presented. Finally, it is discussed that the scenario addressed and the solution presented have great potential, but still need a lot of work and technical considerations.","PeriodicalId":218475,"journal":{"name":"2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Generic Concept for Integrating Voice Assistance Into Smart Therapeutic Interventions\",\"authors\":\"Jens Scheible, Fabian Hofmann, M. Reichert, R. Pryss, Marc Schickler\",\"doi\":\"10.1109/CBMS55023.2022.00017\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Therapeutic Interventions (TIs) play an important role in modern medical and psychological treatments, but their integration into the digital world still shows deficits, e.g., in the integration of the auditory interface. Initiatives to integrate this interface into existing Internet- and Mobile-Based Interventions (IMIs) are largely focused on a small group of Voice Assistants (VAs) and their specific capabilities. To mitigate these drawbacks, the presented concept seamlessly integrates arbitrary VAs into the treatment process of TIs. To this end, an architecture - including a discussion of relevant requirements - is presented that, on the one hand, uses VAs as the only point of contact with patients and, on the other hand, provides a comprehensive web-based backend for Healthcare Providers (HCPs). Based on the architecture, a proof-of-concept implementation using Amazon Alexa is presented. Finally, it is discussed that the scenario addressed and the solution presented have great potential, but still need a lot of work and technical considerations.\",\"PeriodicalId\":218475,\"journal\":{\"name\":\"2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CBMS55023.2022.00017\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMS55023.2022.00017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

治疗干预(ti)在现代医学和心理治疗中发挥着重要作用,但它们与数字世界的整合仍然存在缺陷,例如听觉界面的整合。将该接口集成到现有的基于互联网和移动设备的干预措施(IMIs)中的举措主要集中在一小部分语音助理(VAs)及其特定功能上。为了减轻这些缺点,提出的概念无缝地将任意VAs集成到ti的治疗过程中。为此,本文提出了一种体系结构(包括对相关需求的讨论),该体系结构一方面使用VAs作为与患者的唯一接触点,另一方面为医疗保健提供者(hcp)提供全面的基于web的后端。在此基础上,提出了一个使用Amazon Alexa的概念验证实现。最后,讨论了所处理的场景和所提出的解决方案具有很大的潜力,但仍需要大量的工作和技术考虑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Generic Concept for Integrating Voice Assistance Into Smart Therapeutic Interventions
Therapeutic Interventions (TIs) play an important role in modern medical and psychological treatments, but their integration into the digital world still shows deficits, e.g., in the integration of the auditory interface. Initiatives to integrate this interface into existing Internet- and Mobile-Based Interventions (IMIs) are largely focused on a small group of Voice Assistants (VAs) and their specific capabilities. To mitigate these drawbacks, the presented concept seamlessly integrates arbitrary VAs into the treatment process of TIs. To this end, an architecture - including a discussion of relevant requirements - is presented that, on the one hand, uses VAs as the only point of contact with patients and, on the other hand, provides a comprehensive web-based backend for Healthcare Providers (HCPs). Based on the architecture, a proof-of-concept implementation using Amazon Alexa is presented. Finally, it is discussed that the scenario addressed and the solution presented have great potential, but still need a lot of work and technical considerations.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Ultrasonic Carotid Blood Flow Velocimetry Based on Deep Complex Neural Network Graph-based Regional Feature Enhancing for Abdominal Multi-Organ Segmentation in CT Exploiting AI to make insulin pens smart: injection site recognition and lipodystrophy detection Subgroup Discovery Analysis of Treatment Patterns in Lung Cancer Patients Estimating Predictive Uncertainty in Gastrointestinal Polyp Segmentation
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1