Dias Sofia Balula, Diniz José Alves, Konstantinidis Evdokimos, Savvidis Theodore, Zilidou Vicky, Bamidis Panagiotis D, Grammatikopoulou Athina, Dimitropoulos Kosmas, Grammalidis Nikos, Jaeger Hagen, Stadtschnitzer Michael, Silva Hugo, Telo Gonçalo, Ioakeimidis Ioannis, Ntakakis George, Karayiannis Fotis, Huchet Estelle, Hoermann Vera, Filis Konstantinos, Theodoropoulou Elina, Lyberopoulos George, Kyritsis Konstantinos, Papadopoulos Alexandros, Depoulos Anastasios, Trivedi Dhaval, Chaudhuri Ray K, Klingelhoefer Lisa, Reichmann Heinz, Bostantzopoulou Sevasti, Katsarou Zoe, Iakovakis Dimitrios, Hadjidimitriou Stelios, Charisis Vasileios, Apostolidis George, Hadjileontiadis Leontios J
Faculdade de Motricidade Humana, Centro Interdisciplinar de Performance Humana, Universidade de Lisboa, Lisbon, Portugal.
Lab of Medical Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Front Psychol. 2021 Jan 15;11:612835. doi: 10.3389/fpsyg.2020.612835. eCollection 2020.
Human-Computer Interaction (HCI) and games set a new domain in understanding people's motivations in gaming, behavioral implications of game play, game adaptation to player preferences and needs for increased engaging experiences in the context of HCI serious games (HCI-SGs). When the latter relate with people's health status, they can become a part of their daily life as assistive health status monitoring/enhancement systems. Co-designing HCI-SGs can be seen as a combination of art and science that involves a meticulous collaborative process. The design elements in assistive HCI-SGs for Parkinson's Disease (PD) patients, in particular, are explored in the present work. Within this context, the Game-Based Learning (GBL) design framework is adopted here and its main game-design parameters are explored for the Exergames, Dietarygames, Emotional games, Handwriting games, and Voice games design, drawn from the PD-related i-PROGNOSIS Personalized Game Suite (PGS) (www.i-prognosis.eu) holistic approach. Two main data sources were involved in the study. In particular, the first one includes qualitative data from semi-structured interviews, involving 10 PD patients and four clinicians in the co-creation process of the game design, whereas the second one relates with data from an online questionnaire addressed by 104 participants spanning the whole related spectrum, i.e., PD patients, physicians, software/game developers. Linear regression analysis was employed to identify an adapted GBL framework with the most significant game-design parameters, which efficiently predict the transferability of the PGS beneficial effect to real-life, addressing functional PD symptoms. The findings of this work can assist HCI-SG designers for designing PD-related HCI-SGs, as the most significant game-design factors were identified, in terms of adding value to the role of HCI-SGs in increasing PD patients' quality of life, optimizing the interaction with personalized HCI-SGs and, hence, fostering a collaborative human-computer symbiosis.
人机交互（HCI）与游戏在理解人们的游戏动机、游戏行为影响、游戏对玩家偏好的适应性以及在HCI严肃游戏（HCI-SGs）背景下增强参与体验的需求方面开创了一个新领域。当后者与人们的健康状况相关时，它们可以作为辅助健康状况监测/增强系统成为人们日常生活的一部分。共同设计HCI-SGs可被视为一门艺术与科学的结合，涉及一个细致的协作过程。本文特别探讨了针对帕金森病（PD）患者的辅助HCI-SGs中的设计元素。在此背景下，本文采用了基于游戏的学习（GBL）设计框架，并从与PD相关的i-PROGNOSIS个性化游戏套件（PGS）（www.i-prognosis.eu）的整体方法中探索了其主要游戏设计参数，用于运动游戏、饮食游戏、情感游戏、手写游戏和语音游戏的设计。该研究涉及两个主要数据源。具体而言，第一个数据源包括来自半结构化访谈的定性数据，在游戏设计的共创过程中涉及10名PD患者和4名临床医生，而第二个数据源与104名参与者填写的在线问卷数据相关，这些参与者涵盖了整个相关范围，即PD患者、医生、软件/游戏开发者。采用线性回归分析来确定一个具有最显著游戏设计参数的适应性GBL框架，该框架能够有效地预测PGS有益效果向现实生活的可转移性，解决PD的功能症状。这项工作的发现可以帮助HCI-SG设计师设计与PD相关的HCI-SGs，因为确定了最显著的游戏设计因素，这对于增加HCI-SGs在提高PD患者生活质量方面的作用、优化与个性化HCI-SGs的交互以及促进人机协作共生具有重要意义。
