# Development of assistive self-care robot technologies for people with disabilities

> **NIH NIH F32** · UNIVERSITY OF WASHINGTON · 2021 · $41,925

## Abstract

Towards Autonomy in Daily Living: A Formalism for Intelligent Assistive Feeding Systems
 Applicant PI, Tapomayukh Bhattacharjee
Overview We propose to develop a design space framework and co-design methodology for
the development of assistive self-care robot technologies that are informed by the social model
of disability. Our model of assistive robots in the domain of self-care considers an individual's
social and environmental context, coping processes and other factors that can affect independent
functioning. Our design methods utilize embedded sensing to intelligently respond to these con-
siderations. We specifically focus on assistive feeding tasks, proposing a formalism that enables
a robotic system to feed a person with upper-extremity disability. Our guiding principle is that
human-level interaction is feasible only if the robot itself relies on human-level semantics. We im-
plement this principle by relying on data to learn and develop object-dependent control policies
and timing models for acquiring and transferring a bite to a user at a proper time. The system's ob-
server detects world states and arbitrator invokes different control policies based on these states.
The tangible result will be an intelligent assistive feeding robot whose performance can generalize
to different activities, adapt to user preferences, and recover from failures.
Objectives and Relevance to NIH A design framework for assistive robots would provide for-
malisms that let us address the fundamental challenge of designing robots that are responsive to
context of use and support assisted self-care in a variety of social settings. We combine method-
ologies from human-robot interaction, cognitive science, machine learning, robotics and haptics
with user studies and our formalism to address the following research questions: (Q1) Mechanics
of Feeding-Control Policies: How can control policies be designed for dexterous non-prehensile manipu-
lation of deformable objects such as food? (Q2) Social Aspects of Feeding-Bite Timing: How should an
assistive feeding robot decide the right timing for feeding a user? (Q3) Human-in-the-Loop: How can
human-directed feedback be added into the loop for an autonomous assistive feeding system?
 The proposed work will allow users with upper-arm disabilities to use this system for intelli-
gent assistance with daily feeding tasks. This can in turn help them increase their independence
and autonomy making eating easier and more enjoyable. While we presently focus on this spe-
cific application, the tools and insights we gain can generalize to the fields of robotic assistance
and human-robot interaction across other activities of daily living and instrumental activities of
daily living. Thus, our work is clearly motivated by the intent to improve the quality of health
and life of the aging population and is very relevant to the theme of NIH.
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## Key facts

- **NIH application ID:** 10232054
- **Project number:** 5F32HD101192-02
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Tapomayukh Bhattacharjee
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $41,925
- **Award type:** 5
- **Project period:** 2019-12-19 → 2021-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10232054

## Citation

> US National Institutes of Health, RePORTER application 10232054, Development of assistive self-care robot technologies for people with disabilities (5F32HD101192-02). Retrieved via AI Analytics 2026-06-14 from https://api.ai-analytics.org/grant/nih/10232054. Licensed CC0.

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