ArticleBiomimetics (Basel, Switzerland)2026
Hearing It Right, Doing It Safely: A Reflex-Inspired Safety Gatekeeper for Voice-Controlled Exoskeleton Arm Manipulation.
Article in Biomimetics (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Voice interfaces to anthropomorphic robotic arms are typically evaluated without a formal safety layer, or with safety as a post hoc filter trusting the transcript, leaving transcript corruption unaddressed. This paper presents the DAS3 Neuro-Voice Controller, a voice-driven pipeline for a musculoskeletal arm model, evaluated here as a kinematic surrogate for upper-limb exoskeleton and prosthetic control, built on three commitments: on-device intent classification via a 44 M-parameter DistilBERT classifier over a bounded nine-command vocabulary; a deterministic three-layer Gatekeeper enforcing semantic validation, kinematic feasibility, and hard safety constraints independent of classifier confidence; and an upstream Phonetic Interceptor sanitising characteristic ASR mutilations of anatomical and safety terms ("four arm" → "forearm"). Trained on a class-balanced corpus of 3591 expressions and evaluated on fourteen non-native English speakers, the classifier reached 99.95% top-1 accuracy across 1847 oracle-resolvable utterances; the Gatekeeper reduced Priority Override Failure to 0.0%, rejected 100% of out-of-domain speech, and held false-rejection at 2.02%. Against a keyword-spotter baseline the pipeline delivered a 17.4-fold improvement in end-to-end success; the acoustic front-end remains the main weakness. Upstream input repair and downstream deterministic gating emerge as first-class components of safety-critical voice interfaces for assistive systems.
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