Skip to Main Content (Press Enter)

Logo UNIBS
  • ×
  • Home
  • Persone
  • Strutture
  • Competenze
  • Pubblicazioni
  • Professioni
  • Corsi
  • Insegnamenti
  • Terza Missione

Competenze & Professionalità
Logo UNIBS

|

Competenze & Professionalità

unibs.it
  • ×
  • Home
  • Persone
  • Strutture
  • Competenze
  • Pubblicazioni
  • Professioni
  • Corsi
  • Insegnamenti
  • Terza Missione
  1. Pubblicazioni

Measurement of Human Body Segment Properties Using Low-Cost RGB-D Cameras

Articolo
Data di Pubblicazione:
2025
Abstract:
An open question for the biomechanical research community is accurate estimation of the volume and mass of each body segment of the human body, especially when indirect measurements are based on biomechanical modeling. Traditional methods involve the adoption of anthropometric tables, which describe only the average human shape, or manual measurements, which are time-consuming and depend on the operator. We propose a novel method based on the acquisition of a 3D scan of a subject’s body, which is obtained using a consumer-end RGB-D camera. The body segments’ separation is obtained by combining the body skeleton estimation of BlazePose with a biomechanical-coherent skeletal model, which is defined according to the literature. The volume of each body segment is computed using a 3D Monte Carlo procedure. Results were compared with manual measurement by experts, anthropometric tables, and a model leveraging truncated cone approximations, showing good adherence to reference data with minimal differences (ranging from +0.5 to −1.0 dm3 for the upper limbs, −0.1 to −4.2 dm3 for the thighs, and −0.4 to −2.3 dm3 for the shanks). In addition, we propose a novel indicator based on the computation of equivalent diameters for each body segment, highlighting the importance of gender-specific biomechanical models to account for the chest and pelvis areas of female subjects.
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
body segment parameters, measurement science, anthropometry, biomechanics, body volume estimation, Kinect Azure
Elenco autori:
Nuzzi, Cristina; Ghidelli, Marco; Luchetti, Alessandro; Zanetti, Matteo; Crenna, Francesco; Lancini, Matteo
Autori di Ateneo:
GHIDELLI MARCO
LANCINI MATTEO
Nuzzi Cristina
Link alla scheda completa:
https://iris.unibs.it/handle/11379/623485
Link al Full Text:
https://iris.unibs.it/retrieve/handle/11379/623485/355895/2025_Measurement%20of%20Human%20Body%20Segment%20Properties%20Using%20Low-Cost%20RGB-D%20Cameras%20-%20convertito.pdf
Pubblicato in:
SENSORS
Journal
  • Assistenza
  • Privacy
  • Utilizzo dei cookie
  • Note legali

Realizzato con VIVO | Designed by Cineca | 26.5.1.0