Feasibility of a wearable ultrasound sensor for monitoring tibial cortical bone and calf muscle in long-duration spaceflight: physiological signal versus measurement uncertainty
Year: 2026
Type: preprint
Abstract: Astronauts on six-month missions lose cortical bone and antigravity muscle, yet the reference measurements are taken only before and after flight. We asked whether a wearable ultrasound sensor could detect these changes once the uncertainty of the wearable condition itself is taken into account. We built two-dimensional full-wave simulations with pseudospectral elastic and acoustic solvers: axial transmission on the tibia at 1 MHz, measuring the velocity of the first arriving signal (FAS) at the mid-shaft and at the distal site, and pulse-echo (A-mode) thickness measurement of the medial gastrocnemius at 7.5 MHz. The solvers were first checked against analytical solutions. Expected six-month changes came from spaceflight and bed-rest studies. Soft-tissue thickness changes from fluid shift, probe tilt and shift, coupling-gel thickness and electronic noise were simulated and propagated by a Monte Carlo analysis of a pre-flight/in-flight comparison into a 95% minimum detectable change (MDC). At the mid-shaft tibia the simulated response to the expected 0.8% cortical thinning (−12.6 m/s) was far below the MDC of a single-direction probe (563 m/s) and of a bidirectional probe (95 m/s), and the response to changes of 1–2% was irregular and not grid-converged. At the distal site the response was −1.9 m/s. Probe tilt dominated the tibial uncertainty, in agreement with a closed-form dipping-layer model. For the gastrocnemius the MDC was 0.17 mm (0.40 mm in the worst case), and the expected thickness loss, 0.6 to 1.8 mm depending on how volume loss maps to thickness, exceeded it by a factor of 1.5 to 10. Within the limits of a 2D model, muscle thickness is the more promising quantity for in-flight monitoring, whereas tibial cortical bone cannot be followed reliably with a wearable probe.
Author: De Flumeri, Lucio
Language: English
Subfield: Physiology (medical)
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7225465115