A novel approach to measuring muscle mechanics in vehicle collision conditions

Krašna, Simon (avtor), Đorđević, Srđan (avtor), Hribernik, Marija (avtor), Trajkovski, Ana (avtor)

The aim of the study was to evaluate a novel approach to measuring neck muscle load and activity in vehicle collision conditions. A series of sled tests were performed on 10 healthy volunteers at three severity levels to simulate low-severity frontal impacts. Electrical activity-electromyography (EMG)-and muscle mechanical tension was measured bilaterally on the upper trapezius. A novel mechanical contraction (MC) sensor was used to measure the tension on the muscle surface. The neck extensor loads were estimated based on the inverse dynamics approach. The results showed strong linear correlation (Pearson's coefficient $\overline{r}_P$ = 0.821) between the estimated neck muscle load and the muscle tension measured with the MC sensor. The peak of the estimated neck muscle force delayed 0.2 ± 30.6 ms on average vs. the peak MC sensor signal compared to the average delay of 61.8 ± 37.4 ms vs. the peak EMG signal. The observed differences in EMG and MC sensor collected signals indicate that the MC sensor offers an additional insight into the analysis of the neck muscle load and activity in impact conditions. This approach enables a more detailed assessment of the muscle-tendon complex load of a vehicle occupant in pre-impact and impact conditions.

• Jezik: Angleški jezik
• Ključne besede: biomechanics, vehicle occupant, impact, in vivo, muscle activity, active muscle
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: FS - Fakulteta za strojništvo ; MF - Medicinska fakulteta
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2017
• Št. strani: 17 str.
• Številčenje: Vol. 17, iss. 6, art. 1389
• PID: 20.500.12556/RUL-131084
• UDK: [591.473:614.8]:656.1(045)
• ISSN pri članku: 1424-8220
• DOI: 10.3390/s17061389
• COBISS.SI-ID: 15539483
• Datum objave v RUL: 22.09.2021

Gradivo je del revije

• Naslov: Sensors
• Skrajšan naslov: Sensors
• Založnik: MDPI
• ISSN: 1424-8220
• COBISS.SI-ID: 10176278

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
• Začetek licenciranja: 14.06.2017

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: biomehanika, vozila, potniki, trk, prometne nesreče, mišična aktivnost

Projekti

• Financer: ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
• Številka projekta: P2-0109
• Naslov: Modeliranje v tehniki in medicini