Neil Bezodis

Publications (13) View all

• Source

  Available from: Neil Bezodis

  Article: Excessive fluctuations in knee joint moments during early stance in sprinting are caused by digital filtering procedures.

  Neil E Bezodis, Aki I T Salo, Grant Trewartha
  [show abstract] [hide abstract]
  ABSTRACT: Inverse dynamics analyses are commonly used to understand movement patterns in all forms of gait. The aim of this study was to determine the effect of digital filtering procedures on the knee joint moments calculated during sprinting as an example of the possible influence of data analysis processes on interpretation of movement patterns. Data were obtained from three highly trained sprinters who completed a series of 30m sprints. Ten different combinations of cut-off frequency were applied to the two-dimensional kinematic and kinetic input data with the kinetic cut-off frequency set equal to or higher than the kinematic cut-off frequency. When using the commonly adopted practice of filtering the kinetic data with a higher cut-off frequency than the kinematic data, exaggerated fluctuations in the knee joint moment existed soon after contact. In extreme cases, the knee moved between flexor, extensor and flexor dominance in less than 33ms and through ranges exceeding 500Nm. During an inverse dynamics analysis of locomotion, mismatched cut-off frequencies will likely affect the calculated joint moments if the cut-off frequency applied to the kinematic data is less than the true frequency content, particularly during impact phases. In the example of sprinting, exaggerated fluctuations in the knee joint moment appear to be data processing artefact rather than genuine characteristics of the joint kinetics. When the cut-off frequencies, and thus the frequency content of all input data, are matched, the fluctuations after contact are minimal and such a procedure is suggested for inverse dynamics analyses of gait.
  Gait & posture 03/2013; · 2.58 Impact Factor
• Article: Modeling the stance leg in two-dimensional analyses of sprinting: inclusion of the MTP joint affects joint kinetics.

  Neil E Bezodis, I T Salo A, Grant Trewartha
  [show abstract] [hide abstract]
  ABSTRACT: Two-dimensional analyses of sprint kinetics are commonly undertaken but often ignore the metatarsalphalangeal (MTP) joint and model the foot as a single segment. Due to the linked-segment nature of inverse dynamics analyses, the aim of this study was to investigate the effect of ignoring the MTP joint on the calculated joint kinetics at the other stance leg joints during sprinting. High-speed video and force platform data were collected from four to five trials for each of three international athletes. Resultant joint moments, powers, and net work at the stance leg joints during the first stance phase after block clearance were calculated using three different foot models. By ignoring the MTP joint, peak extensor moments at the ankle, knee, and hip were on average 35% higher (p < .05 for each athlete), 40% lower (p < .05), and 9% higher (p > .05), respectively, than those calculated with the MTP joint included. Peak ankle and knee joint powers and net work at all joints were also significantly (p < .05) different. By ignoring a genuine MTP joint plantar flexor moment, artificially high peak ankle joint moments are calculated, and these also affect the calculated joint kinetics at the knee.
  Journal of applied biomechanics 05/2012; 28(2):222-7. · 0.76 Impact Factor
• Source

  Available from: Neil Bezodis

  Article: Modelling the Stance Leg in 2D Analyses of Sprinting: Inclusion of the MTP Joint Affects Joint Kinetics.

  Neil E Bezodis, Aki I T Salo, Grant Trewarth
  [show abstract] [hide abstract]
  ABSTRACT: Two-dimensional analyses of sprint kinetics are commonly undertaken but often ignore the metatarsal-phalangeal (MTP) joint and model the foot as a single segment. Due to the linked-segment nature of inverse dynamics analyses, the aim of this study was to investigate the effect of ignoring the MTP joint on the calculated joint kinetics at the other stance leg joints during sprinting. High-speed video and force platform data were collected from four to five trials for each of three international athletes. Resultant joint moments, powers and net work at the stance leg joints during the first stance phase after block clearance were calculated using three different foot models. By ignoring the MTP joint, peak extensor moments at the ankle, knee and hip were on average 35% higher (P < 0.05 for each athlete), 40% lower (P < 0.05) and 9% higher (P > 0.05), respectively, than those calculated with the MTP joint included. Peak ankle and knee joint powers and net work at all joints were also significantly (P < 0.05) different. By ignoring a genuine MTP joint plantarflexor moment, artificially high peak ankle joint moments are calculated, and these also affect the calculated joint kinetics at the knee.
  Journal of applied biomechanics 11/2011; · 0.76 Impact Factor
• Source

  Available from: Neil Bezodis

  Article: Choice of sprint start performance measure affects the performance-based ranking within a group of sprinters: which is the most appropriate measure?

  Neil E Bezodis, Aki I T Salo, Grant Trewartha
  [show abstract] [hide abstract]
  ABSTRACT: Sprint start performance has previously been quantified using several different measures. This study aimed to identify whether different measures could influence the performance-based ranking within a group of 12 sprinters, and if so, to identify the most appropriate measure. None of the 10 performance measures ranked all sprinters in the same order; Spearman's rho correlations between different block phase measures ranged from 0.50 to 0.94, and between block phase measures and those obtained beyond block exit from 0.66 to 0.85. Based on the consideration of what each measure quantifies, normalised average horizontal external power was identified as the most appropriate, incorporating both block velocity and the time spent producing this velocity. The accuracy with which these data could be obtained in an externally valid field setting was assessed against force platform criterion data. For an athlete producing 678 +/- 40 W of block power, a carefully set-up manual high-speed video analysis protocol produced systematic and random errors of +5 Wand +/- 24 W, respectively. Since the choice of performance measure could affect the conclusions drawn from a technique analysis, for example the success of an intervention, it is proposed that external power is used to quantify start performance.
  Sports Biomechanics 11/2010; 9(4):258-69. · 0.93 Impact Factor
• Article: EMG sensor location: Does it influence the ability to detect differences in muscle contraction conditions?

  J A Mercer, N Bezodis, D DeLion, T Zachry, M D Rubley
  [show abstract] [hide abstract]
  ABSTRACT: Even though it is well known that electromyography (EMG) characteristics are influenced by electrode placement it is common to use a single pair of sensors per muscle for EMG. This study was designed to determine if the ability to distinguish between contraction conditions was influenced by sensor location. Subjects (n = 10; 27+/-5.3 years; 82+/-13.4 kg; 178+/-7.1 cm) completed six elbow flexor conditions: three isometric contraction intensities (100% maximum effort, 80%, 50%) and three isotonic contraction intensities (heavy weight, 80% and 50% of the weight). Three pairs of electrodes were placed centrally, medially and laterally on the biceps brachii belly in line with the muscle fibers. Isometric contractions were held for 5s, with the middle 3 s analyzed. Isotonic exercises included five repetitions of elbow flexion-extension, with the middle three repetitions analyzed. Average EMG (EMG(AVG)), root mean square EMG (EMG(RMS)) and mean power frequency (MPF) were calculated for each extracted data set. Dependent variables were analyzed using 2 (contraction type) x 3 (intensity) repeated measures ANOVAs per sensor. EMG(AVG) was influenced by the interaction between contraction type and intensity for all sensors (p < 0.05). EMG(RMS) as well as MPF were influenced by the interaction between contraction type and intensity for the lateral and central leads (p < 0.05) but not the medial leads (p > 0.05). Different conclusions could have been reached from the same experiment due to different sensor locations. These differences were primarily related to comparing contraction types (i.e., isotonic vs. isometric).
  Journal of Electromyography and Kinesiology 05/2006; 16(2):198-204. · 1.97 Impact Factor