Arisole publishes research on who can access movement assessment and how markerless motion can be compared openly. Both papers below are posted on SSRN as working papers. They are not described as peer reviewed. Author: Varun Srivastava. Affiliation: Arisole.
How the work relates to Motion Intelligence
Motion Intelligence is Arisole’s name for turning movement events into structured data. Movement Poverty asks who currently gets biomechanical assessment. The markerless gait benchmark asks how computer vision systems can be compared openly and privately — including work that later informs Physical AI evaluation.
Collaborate
Researchers, labs and industry teams can read both papers on SSRN and contact Arisole for collaboration. Book a demo if you want to discuss product surfaces: StrideIQ, Fusion, MotionBench or Motion API.
Papers on SSRN
Movement Poverty: Who Gets to Know How They Move: A Literature Review of Biomechanical Assessment Access, with a Regional Case Study
Varun Srivastava · Arisole · 2026
A literature review of who can access biomechanical assessment, with a regional case study. The paper frames movement knowledge as unequally distributed and argues for more accessible ways to understand how people move — without treating smartphone video as a clinical diagnosis.
Access to biomechanical assessment
Movement knowledge inequality
Regional case study
Motion Intelligence as accessible structured movement data
Srivastava, V. (2026). Movement Poverty: Who Gets to Know How They Move: A Literature Review of Biomechanical Assessment Access, with a Regional Case Study. SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7178778
@misc{srivastava2026movementpoverty,
author = {Srivastava, Varun},
title = {Movement Poverty: Who Gets to Know How They Move: A Literature Review of Biomechanical Assessment Access, with a Regional Case Study},
year = {2026},
howpublished = {SSRN},
url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7178778},
note = {Working paper / preprint. Not described as peer reviewed.}
}
Toward an Open, Privacy-Preserving Benchmark for Markerless Gait Analysis: A Seed Release and Call for Community Contribution (v0.1)
Varun Srivastava · Arisole · 2026
A seed release and call for community contribution toward an open, privacy-preserving benchmark for markerless gait analysis. The work is relevant to computer vision, open movement benchmarks, and robotics / Physical AI research that needs comparable motion evaluation.
Markerless gait analysis
Open movement benchmarks
Privacy-preserving evaluation
Computer vision and Physical AI comparability
Srivastava, V. (2026). Toward an Open, Privacy-Preserving Benchmark for Markerless Gait Analysis: A Seed Release and Call for Community Contribution (v0.1). SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7178738
@misc{srivastava2026markerlessgait,
author = {Srivastava, Varun},
title = {Toward an Open, Privacy-Preserving Benchmark for Markerless Gait Analysis: A Seed Release and Call for Community Contribution (v0.1)},
year = {2026},
howpublished = {SSRN},
url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7178738},
note = {Working paper / preprint. Not described as peer reviewed.}
}