VOLI: Voice Assistant for Quality of Life and Healthcare Improvement in Aging Populations


Overview

According to the latest US Census Bureau predictions, by 2035 older people are projected to outnumber children for the first time in US history. This brings significant societal challenges based on their unique living and health-related conditions stemming from reduced sensory, motor, and cognitive capabilities, as well as multiple chronic conditions. Technology can play a pivotal role in meeting the needs of older adults in ways that preserve their independence. Voice represents a natural choice for interaction between an aging individual and their caregivers, social networks, and healthcare providers, and it becomes key for those with visual or mobility impairment.

We are working on a personalized and context-aware voice-based digital assistant to improve the quality of life and the healthcare of older adults, and consequently, to reduce caregiving burden and optimize the interactions with healthcare and service providers.

We strive for innovations in natural language understanding, deep learning, and human-computer interfaces that leverage information from EHRs, clinical ontologies, and novel patient-level terminologies to support among others the clinical use case of detecting symptom changes and medication side effects.

More Info here: http://voli.ucsd.edu


Funding and External Collaborations

VOLI is a NIH/NSF Smart and Connected Health (SCH) funded by the National Institute of Aging (NIA) at NIH. It is a collaboration between the HXI Lab and a number of experts at UC San Diego’s Qualcomm Instititute, Computer Science and Engineering, and School of Medicine in healthcare, expert systems in clinical care, EHR integration, the aging population, patient monitoring, patient self-report, machine learning for natural language processing and understanding, experimental prototyping, field studies, and software engineering of large-scale systems.


Publications

Nadir Weibel
Nadir Weibel
Associate Professor of Computer Science and Engineering
Chen Chen
Chen Chen
Ph.D. Student
Janet Johnson
Janet Johnson
Ph.D. Candidate