Prostate cancer is one of the most common types of cancer in men, especially those over 65 years old. In the United States, it is estimated that over 190,000 new cases of prostate cancer will be diagnosed, and around 33,000 deaths from prostate cancer, in 2020. Although some types of prostate cancer can grow slowly and locally, thus requiring no treatment, other types of prostate cancer are more aggressive and can grow quickly, thus requiring treatment. Neoadjuvant chemoradiotherapy (nCRT) and total mesorectal excision (TME) are standard treatment of prostate/rectal cancer. Since the quality of life is low for patients undergoing TME, it is preferable for the physician to administer nCRT treatment.
Prof. Hall is developing ultra-low power circuits and sensors for future IoT biosensors. These BioMote sensors are the size of a single grain of rice and will be subcutaneously injected through a 16-gauge needle into interstitial fluid (ISF), the quasi-stationary extracellular fluid surrounding cells composed of nutrients, metabolites, and waste. ISF is highly correlated with blood enabling continuous, long-term biomarker monitoring. The batteryless device will be wirelessly powered through an inductive link that will also be used for bi-directional communication.
Physical therapy is crucial for rehabilitation following many different types of surgery and injury, but it is often severely hampered by lack of access to therapists and lack of adherence to home therapy regimens. Similarly, wellness training and ergonomics training can be crucial components of preventative medicine, but are often not availed of due to a lack of access to proper expertise and guidance. This project aims to develop a computer vision based mobile system that can help people with accurate physical therapy, fitness training and ergonomics, while letting the medical caregivers track progress and compliance of patients.
This project is part of the CWC Connected Health Program in partnership with Kaiser Permanente, UC San Diego Health, Samsung Digital Health and Teradata. The project goal is to develop a scalable Hybrid Edge-Cloud architecture and analytics algorithms to enable highly personalized and contextual virtual care recommendations.
This project is an interdisciplinary research effort led by Dr. Mishra, director of the Neural Engineering & Translation Labs (NEATLabs), UC San Diego, that aims to understand the continuum of mood and attention related fluctuations in humans. The project uses scalable research methods to monitor neuro-cognition and lifestyle (i.e. sleep, physical activity and stress. Using predictive models, the project aims to develop a quantitative, mechanistic and personalized understanding of mood and attention related disorders, and further develop personalized interventions to optimize mental health in humans.
The objective of this project is to enable effective remote monitoring, digital triage and personalized guidance for ambulatory patients with COVID-19 using wearables and machine learning. The project has two components:
The goal of this project is to create multiple systems to improve workplace efficacy of young adults with ASD including a range of workplace communication trainings tools, such as video games, role-playing scenarios, and technology-enabled training systems. The training systems are based on virtual reality (VR) and augmented reality (AR) that will enable high functioning individuals with ASD to develop workplace-appropriate behaviors, such as looking at conversational partners, maintaining interpersonal distance, orienting the body for dyadic and triadic conversations, and providing appropriately timed engagement responses when listening.