How emotion is made and measured

Boehner, Kirsten; DePaula, Rogério; Dourish, Paul; Sengers, Phoebe

doi:10.1016/j.ijhcs.2006.11.016

Cited by 321 publications

(197 citation statements)

References 31 publications

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“…Some people make their facial expression changed little bit from normal state when they pose for photo shooting. For example, we asked to 'pose for the camera' or 'smile for the camera' [36] when we need the photo of anybody. Getting the message to pose for photo, the facial gesture is changed since the patients are ready to pose for photo.…”

Section: Smile For the Cameramentioning

confidence: 99%

Pain Level Detection From Facial Image Captured by Smartphone

Hasan

Ahsan

Ahamed

et al. 2016

Journal of Information Processing

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Accurate symptom of cancer patient in regular basis is highly concern to the medical service provider for clinical decision making such as adjustment of medication. Since patients have limitations to provide self-reported symptoms, we have investigated how mobile phone application can play the vital role to help the patients in this case. We have used facial images captured by smart phone to detect pain level accurately. In this pain detection process, existing algorithms and infrastructure are used for cancer patients to make cost low and user-friendly. The pain management solution is the first mobile-based study as far as we found today. The proposed algorithm has been used to classify faces, which is represented as a weighted combination of Eigenfaces. Here, angular distance, and support vector machines (SVMs) are used for the classification system. In this study, longitudinal data was collected for six months in Bangladesh. Again, cross-sectional pain images were collected from three different countries: Bangladesh, Nepal and the United States. In this study, we found that personalized model for pain assessment performs better for automatic pain assessment. We also got that the training set should contain varying levels of pain in each group: low, medium and high.

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Section: Smile For the Cameramentioning

confidence: 99%

Pain Level Detection From Facial Image Captured by Smartphone

Hasan

Ahsan

Ahamed

et al. 2016

Journal of Information Processing

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“…The firs challenging issue is that the way a certain emotion is expressed generally depends on the speakers, their culture, and their environment [24]. Most work has focused on monolingual emotion classification making an assumption there is no cultural difference among speakers.…”

Section: Modeling the User Emotional Statementioning

confidence: 99%

Modeling the user state for context-aware spoken interaction in ambient assisted living

2014

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Ambient Assisted Living (AAL) systems must provide adapted services easily accessible by a wide variety of users. This can only be possible if the communication between the user and the system is carried out through an interface that is simple, rapid, effective, and robust. Natural language interfaces such as dialog systems fulfil these requisites, as they are based on a spoken conversation that resembles human communication. In this paper, we enhance systems interacting in AAL domains by means of incorporating context-aware conversational agents that consider the external context of the interaction and predict the user's state. The user's state is built on the basis of their emotional state and intention, and it is recognized by means of a module conceived as an intermediate phase between natural language understanding and dialog management in the architecture of the conversational agent. This prediction, carried out for each user turn in the dialog, makes it possible to adapt the system dynamically to the user's needs. We have evaluated our proposal developing a context-aware system adapted to patients suffering from chronic pulmonary diseases, and provide a detailed discussion of the positive influenc of our proposal in the success of the interaction, the information and services provided, as well as the perceived quality.

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“…For such an overview, we refer to the various handbooks and review papers on emotions, affective sciences, and affective neuroscience; e.g., [7][8][9]. In this section, we will touch some of the major works on emotion research, which origin from medicine, biology, physiology, and psychology.…”

Section: History: Lessons To Be Learned and Experiences To Remembermentioning

confidence: 99%

Prerequisites for Affective Signal Processing (ASP) – Part IV

Broek

Zwaag

Healey

et al. 2010

Proceedings of the 1st International Workshop on Bio-Inspired Human-Machine Interfaces and Healthcare Applications

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Abstract. In [1][2][3], a series of prerequisites for affective signal processing (ASP) was defined: validation (e.g., mapping of constructs on signals), triangulation, a physiology-driven approach, contributions of the signal processing community, identification of users, theoretical specification, integration of biosignals, and physical characteristics. This paper defines three additional prerequisites: historical perspective, temporal construction, and real-world baselines.

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How emotion is made and measured

Cited by 321 publications

References 31 publications

Pain Level Detection From Facial Image Captured by Smartphone

Pain Level Detection From Facial Image Captured by Smartphone

Modeling the user state for context-aware spoken interaction in ambient assisted living

Prerequisites for Affective Signal Processing (ASP) – Part IV

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