Functional electrical stimulation of lower limb muscles during rowing provides a means for the cardiovascular conditioning in paraplegia. The possibility of shaping stimulation profiles according to changes in knee angle, so far conceived as changes in seat position, may help circumventing open issues associated with muscle fatigue and movement coordination. Here, we present a subject-specific biomechanical model for the estimation of knee joint angle during indoor rowing. Anthropometric measurements and foot and seat positions are inputs to the model. We tested our model on two samples of elite rowers; 15 able-bodied, and 11 participants in the Rio 2016 Paralympic games. Paralympic rowers presented minor physical disabilities (LTA-PD classification), enabling them to perform the full rowing cycle (with legs, trunks, and arms). Knee angle was estimated from the rowing machine seat position, measured with a linear encoder, and transmitted wirelessly to a computer. Key results indicate the root mean square error (RMSE) between estimated and measured angles did not depend on group and stroke rate ( ). Significantly greater RMSE values were observed, however, within the rowing cycle ( ), reaching on average 8 deg in the mid-recovery phase. Differences between estimated and measured knee angle values resulted in slightly earlier (5%) detection of knee flexion, regardless of the group and stroke rate considered. Offset of knee extension, knee angle at catch and range of knee motion were identified equally well with our model and with inertial sensors. These results suggest our model describes accurately the movement of knee joint during indoor rowing.

Download full-text PDF

Source
http://dx.doi.org/10.1109/TNSRE.2018.2876634DOI Listing

Publication Analysis

Top Keywords

knee angle
16
knee joint
12
indoor rowing
12
knee
10
biomechanical model
8
model estimation
8
estimation knee
8
joint angle
8
angle indoor
8
seat position
8

Similar Publications

Background: Patellofemoral pain syndrome (PFPS) is a common disorder affecting the lower extremity. This study aimed to compare the effects of functional strength training (FST) and standard strength training (SST) in PFPS patients.

Methods: Forty college students (aged 18-30 years) with PFPS and no exercise habits were randomized into FST group (n = 20) and SST group (n = 20).

View Article and Find Full Text PDF

In clinical movement biomechanics, kinematic measurements are collected to characterise the motion of articulating joints and investigate how different factors influence movement patterns. Representative time-series signals are calculated to encapsulate (complex and multidimensional) kinematic datasets succinctly. Exacerbated by numerous difficulties to consistently define joint coordinate frames, the influence of local frame orientation and position on the characteristics of the resultant kinematic signals has been previously proven to be a major limitation.

View Article and Find Full Text PDF

Background: Evaluating the correlation between degenerative meniscus tears and medial meniscus extrusion is necessary to determine the appropriate treatment plan for early-stage knee osteoarthritis. This study evaluated the relationship between degenerative meniscal tears and medial meniscus extrusion in early-stage knee osteoarthritis by using ultrasonography.

Methods: A total of 132 knees from 123 patients with early-stage knee osteoarthritis were evaluated retrospectively.

View Article and Find Full Text PDF

Background: Previous clinical studies suggest that preserving the anterior cruciate ligament (ACL) is crucial for stable knee motion and long-term longevity of the reconstructed knee. The ACL damage or loss often occurs in advanced medial osteoarthritis (OA). This study aimed to investigate the correlation between ACL damage and varus deformity progression as a risk factor for ACL tears in knee OA.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!