The Cadaver in the Machine: The Social Practices of Measurement and Validation in Motion Capture Technology

TL;DR

This paper investigates how motion capture technologies encode and propagate assumptions about human bodies by treating measurement and validation as social practices. Through a systematic literature review of 278 papers and a social practice theory lens, it identifies three historical eras (Foundation, Standardization, Innovation) and six error types that have stabilized measurement and validation practices over time. It shows that concurrent validity and gold-standard references dominate validation in the Innovation Era, while subgroup validity remains underexplored, revealing potential harms and biases. The authors argue that uncovering these hidden assumptions enables more accountable design, broader audits of AI-enabled systems, and the development of sociotechnical interventions to mitigate representational and operational harms.

Abstract

Motion capture systems, used across various domains, make body representations concrete through technical processes. We argue that the measurement of bodies and the validation of measurements for motion capture systems can be understood as social practices. By analyzing the findings of a systematic literature review (N=278) through the lens of social practice theory, we show how these practices, and their varying attention to errors, become ingrained in motion capture design and innovation over time. Moreover, we show how contemporary motion capture systems perpetuate assumptions about human bodies and their movements. We suggest that social practices of measurement and validation are ubiquitous in the development of data- and sensor-driven systems more broadly, and provide this work as a basis for investigating hidden design assumptions and their potential negative consequences in human-computer interaction.

Figures (9)

• Figure 1: The elements of social practices. Sociotechnical practices, like motion capture, inherit assumptions that are baked into their elements, including earlier versions of those elements. Assumptions that give rise to the practice in the first place also spread by way of those elements being combined and recombined. As practices evolve and stabilize, the assumptions that undergird them solidify.
• Figure 2: Stabilizing “voguing” as a distinct dance form 1960s-1980s: critical mass of repetitions.
• Figure 3: The elements of measurement practice for motion capture.
• Figure 4: The elements of validation practice for motion capture.
• Figure 5: Analytical lens: errors provide insight into practices stabilization and assumptions solidification.