Andrea N. Onodera

A method for better positioning bipolar electrodes for lower limb EMG recordings during dynamic contractions

To obtain a high quality EMG acquisition, the signal must be recorded as far away as possible from muscle innervations and tendon zones, which are known to shift during dynamic contractions. This study describes a methodology, using commercial bipolar electrodes, to identify better electrode positions for superficial EMG of lower limb muscles during dynamic contractions. Eight female volunteers participated in this study. Myoelectric signals of the vastus lateralis, gastrocnemius medialis, peroneus longus and tibialis anterior muscles were acquired during maximum isometric contractions using bipolar electrodes. The electrode positions of each muscle were selected assessing SENIAM and then, other positions were located along the length of muscle up and down the SENIAM site. The raw signal (density), the linear envelopes, the RMS value, the motor point site, the position of the IZ and its shift during dynamic contractions were taken into account to select and compare electrode positions. For vastus lateralis and peroneus longus, the best sites were 66% and 25% of muscle length, respectively (similar to SENIAM location). The position of the tibialis anterior electrodes presented the best signal at 47.5% of its length (different from SENIAM location). The position of the gastrocnemius medialis electrodes was at 38% of its length and SENIAM does not specify a precise location for signal acquisition. The proposed method should be considered as another methodological step in every EMG study to guarantee the quality of the signal and subsequent human movement interpretations.

What is the best method for child longitudinal plantar arch assessment and when does arch maturation occur

BACKGROUND The medial longitudinal arch modifies significantly during growth. Nevertheless, authors differ on the age at which the foot acquires the adult-like shape. The best method to assess this arch in children is also controversial. OBJECTIVES Characterize the longitudinal arch of children between 3 and 10 years and compare the applicability of five evaluation methods. METHODS Plantar prints were acquired from 391 healthy preschools children from the University of Sao Paulo, Brazil. We calculated the arch indexes of: Cavanagh and Rodgers, Chipaux-Smirak, Staheli and the Alfa Angle, and compared them with the feet posture assessment. Non-parametric tests were used to compare among methods and ages. Spearman correlation was used to establish relationships among indexes. RESULTS 3 and 4 years old showed a high prevalence of low arches (36-86%). Between 4 and 5 years old, significant difference was observed for all indexes. The indexes presented good correlation among them, although the proportions of the different arch types were different for each age group (p<0.001). CONCLUSIONS The longitudinal arch acquires an adult-like shape progressively, being statistically notorious the moment of medial longitudinal archs formation between 4 and 5 years old. The Chipaux-Smirak Index is the best index to assess childrens feet; it provides a better classification for lower arches and is easily calculated.

Electromyography and kinematic changes of gait cycle at different cadences in diabetic neuropathic individuals

Introduction: Changes in gait cadence caused by challenging situations in daily life might induce higher demand for strength and propulsion in diabetic neuropathic (DN) subjects. Methods: Forty‐six subjects (healthy and DN) walked at two cadences (self‐selected and 25% higher). Kinematic and electromyographic data were obtained from lower limbs and compared across the gait cycle. Results: DN subjects showed a delayed peak in plantarflexor activity along the whole cycle (irrespective of cadence) compared with healthy subjects. However, during the imposed cadence, DN individuals showed reduced ankle range of motion along the entire cycle compared with the self‐selected condition and healthy individuals walking at both cadences (P = 0.002). Conclusions: These findings suggest that when diabetic individuals face a new challenging situation that induces a higher demand for muscle strength and propulsion, the necessary range of motion and neuromuscular control around distal joints are insufficient. Muscle Nerve, 2011

Lower limb electromygraphy and kinematics of neuropathic diabetic patients during real-life activities: Stair negotiation

In this study we investigate the influence of diabetic neuropathy (DN) on lower limb electromyography (EMG) and kinematics during stair negotiation.

Biomechanical variables and perception of comfort in running shoes with different cushioning technologies.

OBJECTIVES To investigate the relationships between the perception of comfort and biomechanical parameters (plantar pressure and ground reaction force) during running with four different types of cushioning technology in running shoes. DESIGN Randomized repeated measures. METHODS Twenty-two men, recreational runners (18-45 years) ran 12km/h with running shoes with four different cushioning systems. Outcome measures included nine items related to perception of comfort and 12 biomechanical measures related to the ground reaction forces and plantar pressures. Repeated measure ANOVAs, Pearson correlation coefficients, and step-wise multiple regression analyses were employed (p≤0.05). RESULTS No significant correlations were found between the perception of comfort and the biomechanical parameters for the four types of investigated shoes. Regression analysis revealed that 56% of the perceived general comfort can be explained by the variables push-off rate and pressure integral over the forefoot (p=0.015) and that 33% of the perception of comfort over the forefoot can be explained by second peak force and push-off rate (p=0.016). CONCLUSIONS The results did not demonstrate significant relationships between the perception of comfort and the biomechanical parameters for the three types of shoes investigated (Gel, Air, and ethylene-vinyl acetate). Only the shoe with Adiprene+ technology had its general comfort and cushioning perception predicted by the loads over the forefoot. Thus, in general, one cannot predict the perception of comfort of a running shoe through impact and plantar pressure received.

The influence of shoe upper construction on the plantar pressure distribution during running

One of the main interests in studying running shoes is to investigate the effects of manipulating physical and mechanical properties of the outsole (Cheung & Ng, 2008; Wiegerinck et al., 2009). The...

Immediate effects of EVA midsole resilience and upper shoe structure on running biomechanics: a machine learning approach

Background Resilience of midsole material and the upper structure of the shoe are conceptual characteristics that can interfere in running biomechanics patterns. Artificial intelligence techniques can capture features from the entire waveform, adding new perspective for biomechanical analysis. This study tested the influence of shoe midsole resilience and upper structure on running kinematics and kinetics of non-professional runners by using feature selection, information gain, and artificial neural network analysis. Methods Twenty-seven experienced male runners (63 ± 44 km/week run) ran in four-shoe design that combined two resilience-cushioning materials (low and high) and two uppers (minimalist and structured). Kinematic data was acquired by six infrared cameras at 300 Hz, and ground reaction forces were acquired by two force plates at 1,200 Hz. We conducted a Machine Learning analysis to identify features from the complete kinematic and kinetic time series and from 42 discrete variables that had better discriminate the four shoes studied. For that analysis, we built an input data matrix of dimensions 1,080 (10 trials × 4 shoes × 27 subjects) × 1,254 (3 joints × 3 planes of movement × 101 data points + 3 vectors forces × 101 data points + 42 discrete calculated kinetic and kinematic features). Results The applied feature selection by information gain and artificial neural networks successfully differentiated the two resilience materials using 200(16%) biomechanical variables with an accuracy of 84.8% by detecting alterations of running biomechanics, and the two upper structures with an accuracy of 93.9%. Discussion The discrimination of midsole resilience resulted in lower accuracy levels than did the discrimination of the shoe uppers. In both cases, the ground reaction forces were among the 25 most relevant features. The resilience of the cushioning material caused significant effects on initial heel impact, while the effects of different uppers were distributed along the stance phase of running. Biomechanical changes due to shoe midsole resilience seemed to be subject-dependent, while those due to upper structure seemed to be subject-independent.