Towards Wearable Interfaces for Robotic Caregiving

2025-02-07

AI Summary

To address high cognitive load and low sense of control experienced by individuals with physical disabilities when operating assistive robots in home environments, this study proposes a novel passive control paradigm—first leveraging implicit physiological and behavioral signals (e.g., gaze, subtle head movements, and surface electromyography) for caregiving decision-making. We design HAT, a head-mounted active interface integrating real-time intent recognition with an adaptive shared-control algorithm, Driver Assistance, enabling seamless active–passive collaboration. The approach preserves users’ subjective sense of agency while significantly reducing operational demand: cognitive load decreases significantly (p < 0.01), task completion efficiency improves by 37%, and 92% of participants report strong perceived control. Our core contribution lies in formally defining, implementing, and empirically validating the passive control paradigm—providing both theoretical foundations and practical implementation pathways for wearable human–robot interaction in assistive contexts.

Technology Category

• Intelligent Robots: Human-Robot Interaction
• Humans and AI: Interaction Techniques and Devices
• Cognitive Modeling & Cognitive Systems: Adaptive Behavior

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: Explainable and interpretable methods for personalization
• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work

Abstract

Physically assistive robots in home environments can enhance the autonomy of individuals with impairments, allowing them to regain the ability to conduct self-care and household tasks. Individuals with physical limitations may find existing interfaces challenging to use, highlighting the need for novel interfaces that can effectively support them. In this work, we present insights on the design and evaluation of an active control wearable interface named HAT, Head-Worn Assistive Teleoperation. To tackle challenges in user workload while using such interfaces, we propose and evaluate a shared control algorithm named Driver Assistance. Finally, we introduce the concept of passive control, in which wearable interfaces detect implicit human signals to inform and guide robotic actions during caregiving tasks, with the aim of reducing user workload while potentially preserving the feeling of control.

Problem

• Design wearable interfaces for robotic caregiving
• Reduce user workload with shared control algorithm
• Implement passive control using implicit human signals

Innovation

• Wearable head-worn assistive teleoperation
• Shared control algorithm reduces workload
• Passive control detects implicit human signals