Supporting remote therapeutic interventions with voice assistant technology

Fischer, Jens (2019) Supporting remote therapeutic interventions with voice assistant technology. Bachelor thesis, Ulm University.

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Nowadays, digital personal assistants are incorporated in many devices. Smart TVs, smartphones and stand-alone voice assistants like Amazon Alexa allow owners to control their smart home systems, play music on command or lookup information on the internet via voice queries. Using custom skills from various third-party vendors, almost any company can have a skill supporting the needs of their customers or control their devices. Furthermore, therapeutic interventions represent a vital part of most therapies, but there are some underlying struggles during therapies for which therapists can utilize the support of smart mobile devices. As an extension of an already existing system called Albatros, its features have been converted into an custom Alexa skill called remote interventions. But voice assistants can do more than improving everyday life, like helping people during medical therapies. A vital part of such therapies are therapeutic interventions, but therapists often face struggles when monitoring a patients progress and results. To overcome this problem, an existing system called Albatros allows a therapist to review the patients status. As an extension to the existing Albatros system, its features have been incorporated into a custom Alexa skill called remote interventions. Aiming to contribute to the proof of concept, the objective of this thesis is to demonstrate the development process of a custom Alexa skill which implements the features of retrieving exercises, allowing patients to record feedback via a smart speaker which can then be accessed by the therapist. With the addition of a notification feature the system also supports patients in remembering how and when to do their exercises properly. Due to the proof of concept nature of the project, apart from the actual development process, an analysis of whether or not the ideas and features translate well into a voice driven platform is performed.

Item Type: Thesis (Bachelor)
Subjects: DBIS Research > Master and Phd-Thesis
Divisions: Faculty of Engineering, Electronics and Computer Science > Institute of Databases and Informations Systems > DBIS Research and Teaching > DBIS Research > Master and Phd-Thesis
Depositing User: Herr Marc Schickler
Date Deposited: 11 Nov 2019 13:54
Last Modified: 11 Nov 2019 13:54

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