The Problem Individuals with neurological disorders often face challenges of loss of independence due to motor and non-motor impairments and dysfunctions, and thus need ongoing rehabilitation and assistance in the community. These patients may struggle with community mobility, daily life activities, walking, and balancing as well as cognitive impairments, leading to reduced quality of life and increased burden to their caregivers, partners, and families. The Approach & Population My research focuses on developing wearable and AIpowered digital health solutions to help individuals with neurological disorders, especially stroke patients and patients with Parkinson’s disease, in their rehabilitation therapies as well as in the community. My research group works on the following research topics: designing and validating smart wearable devices and sensor systems to improve their gait and balance clinical outcomes to increase their independence in living. developing wearable-derived digital biomarkers and predictive AI for remote patient monitoring on functional outcomes, such as their mobility and daily activities, as well as abnormal pain and effectiveness of medication and intervention. Societal Impact I aim to advance patient health through interdisciplinary approaches that integrate engineering, health, and clinical knowledge to develop, validate, and translate wearable and AI-powered digital health solutions to support clinicians in decision-making and assist patients in the clinic and community. Wearable-derived Digital Biomarkers and Predictive AI “I look forward to working with other Lehigh faculty to collaborate on projects, community partners to test our technologies, and donors to collaborate with us in improving clinical and functional outcomes for individuals with Parkinson’s and stroke and transform their health with wearables and AI.” - Rui Hua, PhD Short Term Impact My previous and current work includes the following areas: Smart wearable devices: Development and validation of smart insoles to support patients with Parkinson’s disease, including gait analysis, fall-risk estimation, automation of clinical assessments, and daily activity monitoring. This research was conducted in partnership with local community organizations, including a church-based support group and the Rock Steady Boxing gym. The work has been featured in national and international outlets, including IEEE Spectrum. Remote patient monitoring: Development of novel digital biomarkers, including wearable-derived biorhythms and predictive AI methods, to enable early identification of postoperative complications. This work has been featured by multiple news outlets, including The Washington Post. Longer Term Impact Working closely with Good Shepherd Rehabilitation Hospital in the Lehigh Valley and other clinical or community partners, my research will develop, validate and translate the wearable and AI-powered digital health solutions into real-world benefit to patients in their rehabilitation and daily life. For more information visit https://health.lehigh.edu/research-partners or email INRSRCH@lehigh.edu 16 Data Driven Innovation: Establish the connection between social interaction & relationships and health & well-being, improving community health outcomes. Community/Culture: Help the disabled improve their social connections, benefitting them, their friends and families, and those around them.
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