ATSA-ESI: Assistive Technology Supporting Aging with Emotional and Social Intelligence

在过去的12年里，我一直在开发复杂的辅助技术（AT），旨在帮助患有痴呆症（如阿尔茨海默氏症）的老年人。越来越多的老年人口给医疗保健系统带来了巨大压力，也给非正式照料者（例如在家照顾配偶/父母的配偶/子女）带来了不可持续的负担。我开发的技术可以提供老年人的自主和独立，从而使非正式的护理人员摆脱部分负担，并降低医疗成本。******已经取得了很大的进展，但在这些设备有效和可用之前还有很长的路要走。本研究旨在建立一个从工程学、心理学和社会学的角度对辅助技术（AT）进行老年护理的统一操作模型。社交、情感和情感智能的概念越来越多地在追求有效的人机交互（包括AT）方面发挥着关键作用。对于AT的发展，已知这些观念对痴呆症患者的行为有重大影响。例如，由于阿尔茨海默病干扰了记忆，它通常会导致一个人扮演过去的身份，否则治疗这样的人会产生不和谐，导致冲突、压力和抑郁，当然也会导致AT不被收养。为了解决这个问题，我开发了人工智能系统，将社会和情感因素整合到包括AT在内的人类互动系统中。我利用概率和决策理论的序列动力学模型来开发这些系统。******未来五年我的研究将以社会心理学理论为指导，专注于群体过程模型的理论和实践发展，具体应用于老龄化的AT。我将沿着三个关键途径工作：个人群体中的情感分层建模和特定辅助技术的应用，来自个人和群体互动的传感器数据的用户和上下文模型的机器学习，以及基于社会心理学原理的群体过程模型的开发，这些模型一般超越了AT，并应用于社交网络。我目前支持的研究特别关注个人互动层面的社会情感问题（例如，一个人参与一项活动），并以用户评估为重点。在这个建议中，我解决了个人群体建模的问题，超越了需要照顾的人，包括他们的非正式照顾者，他们的医生，专业照顾者，后代，兄弟姐妹，邻居和社区。基于社会心理学理论，我将开发和测试老年人社会网络模型，以提供更有效和量身定制的护理。这项工作将与我的其他基金资助的其他更以个人为导向的工作相吻合

For the past twelve years I have been building sophisticated assistive technology (AT) designed to assist elderly persons with dementia (e.g. Alzheimer's). An increasingly elderly population is placing a significant strain on the healthcare system, and an unsustainable burden on informal caregivers (e.g. spouses/children caring for their spouse/parent at home). I develop technologies that can provide autonomy and independence in aging, thereby releasing informal carers from part of this burden, and decreasing healthcare costs.******Much progress has been made, but there is a long way to go before these devices are effective and usable. This proposal is to build a unified operational model of engineering, psychological and sociological perspectives on assistive technology (AT) for elder care. Increasingly, the notions of social, emotional and affective intelligence are playing a key role in the pursuit of effective human-machine interaction, including AT. For AT development, these notions are known to have a major impact on the actions of persons with dementia. For example, as Alzheimer's disease interferes with memory, it can often result in a person enacting a past identity, and treating such a person otherwise creates dissonance leading to conflict, stress, and depression, and certainly to AT non-adoption. To handle this, I develop artificially intelligent systems that integrate social and emotional factors into human-interactive systems including AT. I develop these systems using a foundation of probabilistic and decision theoretic sequential dynamical models. ******The next five years of my research will focus on the theoretical and practical development of group process models, guided by social-psychological theory, with specific application to AT for aging. I will work along three key avenues: hierarchical modelling of sentiment in groups of individuals and applications to specific assistive technologies, machine learning of user and context models from sensor data of individual and group interactions, and development of models of group processes in general beyond AT, based on social-psychological principles, with application to social networks. My currently supported research looks specifically at socio-emotional issues at the level of individual interactions (e.g. a single individual engaged in a single activity), and with a user-evaluative focus. In this proposal, I tackle the problem of modelling groups of individuals, going beyond the person in need of care to include their informal caregiver, their doctor, professional carer, offspring, siblings, neighbours and community. Based on social-psychological theory, I will develop and test models of social networks of elderly persons to provide more effective and tailored care. This work will dovetail with the other, more individual-oriented work funded by my other grants.**