Deliver a personalized, remote wellbeing program leveraging computer vision and AI to build physical and emotional resilience and aid recovery in vulnerable older adults impacted by COVID-19

我们的目标是开发并提供一个个性化的远程健康计划，利用计算机视觉和尖端的情感人工智能测试工具，帮助受COVID-19影响的弱势老年人建立身体和情感弹性，帮助他们恢复健康。这个项目的动机是：1。解决老年人在社会参与、安全和监督的环境中的依从性问题。为了开发创新技术，有效地提供家庭健康计划，60岁以上的成年人是受COVID-19影响最严重的群体之一。这不仅表现在死亡人数或感染率上，还表现在他们接受的护理的变化、保持联系的能力以及对疾病和死亡的焦虑上（来源：世卫组织）。“如果运动是一种药丸，它将是有史以来最具成本效益的药物。”然而，开这种“药丸”的最大挑战是坚持。目前最接近我们的最先进技术是计算机视觉——一个训练计算机解释和理解视觉世界的人工智能领域。它的应用范围从自动驾驶汽车到医疗诊断。然而，这种新兴技术在很大程度上还没有触及到健康领域。我们不仅希望成为使用计算机视觉进行姿势估计和身体跟踪的先行者，而且还希望使用情感AI测试方法以独特的方式有效地测试结果。

We aim to develop and deliver a **personalized, remote wellbeing program** leveraging **computer vision** and cutting-edge **emotional AI testing tools** to build physical and emotional resilience and aid recovery in vulnerable older adults impacted by COVID-19\.The motivation for this project is:1. To solve for adherence among older adults in a socially engaging, safe and supervised setting2. To develop innovative technologies to effectively deliver at-home wellbeing programsOlder adults aged 60+ are one of the most severely affected groups from COVID-19\. This is not just manifested in the death toll or infection rate but also the change in the care they receive, their ability to stay connected, and anxiety of illness and death (source:WHO). "If exercise were a pill, it would be the most cost-effective drug ever invented" however the biggest challenge in prescribing this "pill" is that of adherence.Our nearest current state-of-the-art is Computer Vision-a field of artificial intelligence that trains computers to interpret and understand the visual world. Its applications range from self-driving cars to medical diagnostics. However, the field of wellbeing has largely remained untouched by this emerging technology. We not only wish to be the early movers in the using Computer vision for pose estimation and body tracking but also effectively test the outcomes in a unique way using emotional AI testing methods.