MSc Psychological Research PhD - Establishing a role for social robots in healthy independent ageing

这个1+3博士研究生项目的目的是解决老年人在与社交机器人互动时神经认知功能的灵活性和适应性，以确定如何最好地将机器人引入这一群体，以最大限度地提高吸收率，效用和长期使用。这是通过对健康老年人进行问卷调查、长期培训、心理生理和基于大脑的措施以及机器人行业研究实习相结合来实现的。我在这3年中的任务将涉及开发复杂的行为和基于大脑的措施来探索1）老年人如何感知社交辅助机器人并与之互动，2）这些认知和互动如何随着时间的推移而发展（或分解）。在此过程中，我将加深对眼动追踪和行为方法的理解，并获得功能性神经成像和其他电生理技术的专业知识（如肌电图）这个1+3学生项目的研究成果有望帮助阐明如何设计，引入和使用联合收割机AI与社交机器人相结合的复杂的新数字技术，以最好地帮助老年人保持健康，通过更清楚地了解老年人如何看待社交机器人并与之互动，应该有可能鼓励健康老年人在家庭环境中长期接受和融入这些代理。该项目的发现将直接告知并促进我们对数字创新如何帮助（或阻碍）我们在老年保持独立生活的能力的理解。研究结果还应该提供关于为什么某些数字创新可能不被公众的不同部门接受的有价值的见解。建议的方法为了最好地了解健康老年人对社交机器人的态度，我们将通过问卷调查获得接受，信任和参与的措施（例如，Nomura等人，2008; Bartneck等人，2009年）。在这样做的过程中，我们将阐明社会机器人在人群中的感知范围和限制。参与者将参加纵向培训研究（4-8周），其中他们定期来到实验室参与与机器人的互动。通过眼动追踪技术，我们将深入了解用户在人机交互过程中的注意力和参与度。通过采用肌电图（EMG），我们可以测量对机器人的内隐情绪反应（Kirsch等人，2016）。通过部署运动协调任务（例如模仿任务），我们将确定个体将机器人拟人化的程度（Klapper等人，2014）。最后，通过功能性磁共振成像（fMRI），我们将深入了解与机器人持续的社会互动可能导致的大脑变化。重要的是，这些措施中的每一个都可以在长期训练/暴露干预之前、期间和之后使用，以获得对这些个体的社会神经认知过程的可塑性和适应性的有价值的见解。

The aim of this 1+3 PhD studentship is to address the flexibility and adaptability of older individuals' neurocognitive functioning when interacting with social robots, in order to determine how best to introduce robots to this cohort to maximise uptake, utility, and longstanding use. This is achieved through a combination of questionnaires, long-term training, psychophysiological and brain-based measures with healthy older adults, and a robotics industry research internship.My task during these 3 years will involve developing sophisticated behavioural and brain-based measures to probe 1) how older individuals perceive and interact with socially assistive robots, and 2) how these perceptions and interactions develop (or break down) over time. In doing so, I will deepen my understanding of eye-tracking and behavioural methods, and acquire expertise with functional neuroimaging and additional electrophysiological techniques (such as electromyography)The research outcomes from this 1+3 studentship promise to help illuminate how sophisticated new digital technologies that combine AI with social robotics might be designed, introduced, and used, to best help older individuals maintain healthy, independent lives.By gaining a clearer understanding of how older adults perceive and interact with social robots, it should be possible to encourage longer-term acceptance and integration of these agents in the home environment of healthy older individuals. The findings from this project stand to directly inform and advance our understanding of the ways in which digital innovations can help (or hinder) our capacity to maintain independent lives in advanced age. The findings should also provide valuable insights regarding why certain digital innovations may not be accepted by different sectors of general public Proposed MethodologyTo build the best understanding of the attitudes of healthy older adults towards social robots, we will obtain measures of acceptance, trust, and engagement through questionnaires (e.g., Nomura et al., 2008; Bartneck et al., 2009). In doing so, we will shed light on the perceived scope and limits of social robots within the population. Participants will partake in longitudinal training studies (4-8 weeks) wherein they regularly come to the laboratory to partake in interactions with a robot. Through eye-tracking technology, we will gain insight into the attention and engagement of users during human-robot interactions. By employing electromyography (EMG) we can measure implicit emotional responses to the robots (Kirsch et al., 2016). Through the deployment of motor coordination tasks (e.g. mimicry tasks) we will determine the extent to which individuals anthropomorphise the robots (Klapper et al., 2014). Finally, through functional magnetic resonance imaging (fMRI), we will gain insight into brain-based changes that may occur as a result of ongoing social interactions with a robot. Importantly, each of these measures can be used before, during, and after the longterm training/exposure intervention to gain valuable insights to the plasticity and adaptability of social neurocognitive processes in these individuals.