| Literature DB >> 30539133 |
Satoru Hashizume1, Hiroaki Hobara1, Yoshiyuki Kobayashi1, Mitsunori Tada1, Masaaki Mochimaru1.
Abstract
The inter-individual variability of running technique is an important factor affecting the negative work of lower extremity joints that leads to muscle damage. Our study examines the relationships between the negative work of the lower extremity joints and the associated mechanical parameters that account for inter-individual variability in the negative work. Twenty-four young male adults were asked to run on a runway at a speed of 3.0 m·s -1 . Multiple linear regression analysis was conducted to examine the relationships between the negative work and the associated mechanical parameters for each lower extremity joint. With regards to the results, 76.3% of inter-individual variability in the negative work of the hip joint was accounted for by inter-individual variabilities in the corresponding moment (25.4%) and duration (50.9%). For the knee joint, the inter-individual variabilities in the moment (40.6%), angular velocity (24.5%), and duration (23.8%) accounted for 88.9% of inter-individual variability in the negative work. The inter-individual variability in the moment of the ankle joint alone accounted for 89.3% of the inter-individual variability in the corresponding negative work. These results suggest that runners can change the negative work by adapting their running techniques to influence the relevant mechanical parameter values; however, major parameters corresponding to the change in the negative work are not the same among the lower extremity joints.Entities:
Keywords: inverse dynamics; lower extremity joint; multiple linear regression analysis; running-related injury
Year: 2018 PMID: 30539133 PMCID: PMC6277236 DOI: 10.1055/a-0669-0885
Source DB: PubMed Journal: Sports Med Int Open ISSN: 2367-1890
Fig. 1Experimental setup for data collection. Two sets of photocells were placed before and after the force platforms that were embedded on the runway. The distance between the two sets of photocells was set at 5.0 m. The time when each participant passed through this distance was measured using the photocells.
Fig. 2Typical time-series power, moment, and angular velocity of each lower extremity joint. The subject whose negative work was the closest to the corresponding average value was selected as typical for each lower extremity joint. The shaded area represents the duration over which negative power was generated.
Table 1 Means, standard deviations (SDs) and 95% CIs of calculated mechanical parameters.
| Hip joint (95% CI) | Knee joint (95% CI) | Ankle joint (95% CI) | |
|---|---|---|---|
| Negative work (J) | –15.2±7.7 (–19.9, –10.4) | –33.5±10.2 (–39.8, –27.2) | –22.0±7.6 (–26.7, –17.2) |
| Amplitude of negative power (W) | –82.2±33.8 (–103.2, –61.3) | –480.3±136.4 (–564.8, –395.8) | –167.7±73.8 (–213.5, –122.0) |
| Duration of negative power (ms) | 169±35 (148, 191) | 72±14 (63, 81) | 134±13 (126, 142) |
| Moment of joint (N·m) | –11.7±13.3 (–19.9, –3.5) | 94.9±14.5 (85.9, 103.9) | 63.3±20.1 (50.9, 75.8) |
| Angular velocity of joint (rad·s −1 ) | 3.18±0.42 (2.92, 3.44) | –5.61±0.93 (–6.19, –5.03) | –1.39±1.40 (–2.26, –0.52) |
Table 2 Partial regression coefficient ( b ), standardized partial regression coefficient (b* ) and correlation coefficient ( r ) for each mechanical parameter.
|
|
|
| ||
|---|---|---|---|---|
| Hip joint | Moment of joint | −0.225 | −0.391 | −0.649 |
| Angular velocity of joint | - | - | - | |
| Duration of negative power | −0.141 | −0.639 | −0.797 | |
| Knee joint | Moment of joint | −0.385 | −0.551 | −0.736 |
| Angular velocity of joint | 5.517 | 0.506 | 0.485 | |
| Duration of negative power | −0.444 | −0.623 | −0.382 | |
| Ankle joint | Moment of joint | 0.359 | 0.945 | 0.945 |
| Angular velocity of joint | - | - | - | |
| Duration of negative power | - | - | - |
Fig. 3Contribution of mechanical parameters for each lower extremity joint. Stacked black, gray, and white bars represent the contributions of the moment, angular velocity, and duration of the negative power, respectively. Statistically, the sum of the contributions (a hundredfold of the product of the standardized partial regression coefficient and the correlation coefficient) equals a hundredfold of the coefficient of determination.