Evaluation of spoken dialogue technology for real-time health data collection.
Evaluation of spoken dialogue technology for real-time health data collection.
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DOI：
10.2196/jmir.8.4.e30
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发表时间：
2006-12-11
影响因子：
7.4
通讯作者：
Levin A
中科院分区：
文献类型：
--
作者：
Levin E;Levin A
对患者体验的实时评估是医疗保健、生活质量、行为科学以及新药和治疗开发研究的重要方法。生态瞬时评估是一种方法，允许实时评估的经验和行为在一个主题的自然环境。最近，引入了电子数据收集技术，包括利用交互式语音应答的系统。该项目的目的是评估口语对话方法，用于实时收集患者信息，用于健康、行为和生活方式研究和监测。虽然数据收集过程的管理是基于互联网的，但这个额外的电子健康通信渠道是基于电话上的自然语言对话，对话系统利用自动语音识别技术。在这项研究中，我们实施了一个对话系统，用于患者对慢性疼痛的评估和监测。对24名志愿者进行了疼痛监测语音日记可用性的实验评估。志愿者被要求在两周的时间内使用该系统进行10次会话；实际上，每个科目的会议数从1次到20次不等。受试者被要求在回答系统的问题时讲述他们过去的疼痛经历，或者使用疼痛专家提供的九种医疗场景中的一种作为指导，这些场景包括偏头痛、背痛、手术后疼痛（膝盖损伤）、癌症和化疗相关的疼痛。从24名志愿者中，我们共收集了177个对话会话：171个会话完成，而在其他6个会话中，来电者挂断了电话。共有2437个对话回合，其中一个对话回合对应一个系统提示和一个用户话语。数据捕获率（测量自动填充的槽的百分比）为98%，而其他2%被标记为转录。在用户选择“这些都不是”选项的语音中，70%对应于“疼痛类型”插槽，20%对应于“症状”插槽，10%对应于“身体部位”插槽，表明这些是词汇外率最高的语法。这项可行性研究的结果表明，高自动化程度（研究中为98%）可以实现所需的数据准确性，用户确实能够利用灵活的界面，随着用户体验的增加，会话在会话持续时间和避免麻烦的对话情况方面变得越来越高效。
A real-time assessment of patients’ experiences is an important methodology for studies in health care, quality of life, behavioral sciences, and new drug and treatment development. Ecological momentary assessment is a methodology that allows for real-time assessment of experience and behavior in a subject’s natural environment. Recently, electronic data collection techniques have been introduced, including systems utilizing interactive voice response. The objective of this project was evaluation of spoken dialogue methodology for real-time data collection of information from patients for health, behavioral, and lifestyle studies and monitoring. While the management of the data collection process was Internet-based, this additional eHealth communication channel was based on over-the-phone natural language conversation with a dialogue system utilizing automated speech recognition technology. For this study we implemented a dialogue system for patients’ assessment and monitoring of chronic pain. Experimental evaluation of usability of the Pain Monitoring Voice Diary was performed with 24 volunteers. The volunteers were asked to contribute 10 sessions with the system over a period of 2 weeks; in practice, the number of sessions per subject ranged from 1 to 20. The subjects were asked to either relate to pain episodes in their past while answering the system’s questions, or use as a guidance one of nine provided medical scenarios compiled by a pain specialist, ranging from migraines and back pain to post-surgical pain (knee injury) and cancer- and chemotherapy-related afflictions. From 24 volunteers, we collected a total of 177 dialogue sessions: 171 sessions were completed, while the caller hung up in the other 6 sessions. There were a total of 2437 dialogue turns, where a dialogue turn corresponds to one system prompt and one user utterance. The data capture rate, measuring the percentage of slots filled automatically, was 98%, while the other 2% were flagged for transcription. Among the utterances sent to transcription, where the user had opted for the “none of those” option, 70% corresponded to the “type of pain” slot, 20% to the “symptoms” slot, and 10% to the “body part” slot, indicating that those are the grammars with the highest out-of-vocabulary rate. The results of this feasibility study indicated that desired accuracy of data can be achieved with a high degree of automation (98% in the study) and that the users were indeed capable of utilizing the flexible interface, the sessions becoming more and more efficient as users’ experience increased, both in terms of session duration and avoidance of troublesome dialogue situations.
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影响因子：
7.4
作者：
Paul J;Seib R;Prescott T
通讯作者：
Prescott T
影响因子：
6.1
作者：
Davis, MP;Walsh, D
通讯作者：
Walsh, D
影响因子：
2.3
作者：
Collins, RL;Kashdan, TB;Gollnisch, G
通讯作者：
Gollnisch, G
影响因子：
7.4
作者：
DAUT, RL;CLEELAND, CS;FLANERY, RC
通讯作者：
FLANERY, RC
影响因子：
105.7
作者：
Stone, AA;Shiffman, S;Hufford, MR
通讯作者：
Hufford, MR