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Somatic AI research for embodied movement and human–AI co-creation.
Founded by Hanna Zhu, Somatic-AI Lab connects somatic practice, movement computing and generative systems through source-linked research, field synthesis and practitioner guidance.
This week · Pulse
Mon / Tue / Wed drops — news scan, community field notes, and a plain-language explainer. Updates weekly (Mon–Wed). Public categories: news-digest, community-news, popular-explainer.
Motion AI Moves from One-Shot Generation toward Choreographic Choice, Better Language Tests and Local Editing
Three preprints published between 4 and 10 August 2026 mark a practical change in human-motion AI. CustomDance lets a person choose and refine phrases rather than accepting a complete generated dance; MRBench tests whether models can connect movement to language at different levels of detail; and Un…
Community Signals: Synthetic Wearables, Pressure from Video, Motion-Capture Audits and Multiple Possible Futures
Four releases from 5–11 August 2026 widen what counts as motion data. VSMP-IMU turns video into controllable synthetic wearable signals; HOPE estimates changing hand pressure from ordinary monocular video; a contextual-auditing paper asks how motion-capture skeletons should be judged when “ground tr…
Why the Best Movement Edit May Have More Than One Right Answer
If you ask an AI to “make this reach softer,” there is no single correct edited movement waiting to be found. The reach could take longer, travel through a rounder pathway, use less acceleration, reorganise support through the feet, allow the ribs to follow, or change how the hand meets its destinat…
This month · Long-form
The Agnosticism Turn: Motion AI Is Removing Its Fixed Assumptions About Bodies, Sensors and Formats
The defining development in motion AI during July 2026 was the removal of fixed assumptions. Four independent research groups published systems that each dropped a constraint previously treated as structural: EquiFusion removed the fixed skeleton, WHIP removed the fixed sensor configuration, Two2Fou…
Somaesthetics and the Trained Perceiver: Why Better Sensors Do Not Produce Better Perception
Richard Shusterman's philosophical project of somaesthetics rests on a claim that cuts against an assumption widespread in motion AI: that bodily perception is not fixed equipment but a trainable capacity, and that improving it is a distinct undertaking from improving what is measured. This analysis…
The Movement Is a Field, Not a Line: Motor Abundance and Generative Uncertainty
Connection type: Structural correspondence between task-stabilising variation in biological movement and multi-solution representations in generative motion AI. The motor-control evidence and the machine-learning evidence are each established in their own domains; the claim that practitioner-guided …
The Choice Set: A Somatic Counterfactual Editor for Testing What a Movement Must Preserve
What if the most useful output from a movement model were not its best answer, but three defensible alternatives that force a practitioner to discover what they meant?
Choosing Sensors for Movement Practice: What Consumer Devices Can and Cannot Tell You
Movement practitioners considering wearable sensing usually ask which device to buy. The more useful question is which signal type the device produces, because that determines what can be measured at all. This guide sets out four signal types available in consumer and prosumer hardware — inertial, p…
Kristina Höök and Soma Design: Building Interaction Around the Sentient Body
Kristina Höök is Professor of Interaction Design at KTH Royal Institute of Technology in Stockholm, where she leads the Somaesthetic Design Research Group. Her central contribution is soma design — a design practice, set out in Designing with the Body: Somaesthetic Interaction Design (MIT Press, 201…