Impact of Asthma on Plantar Pressures in a Sample of Adult Patients: A Case-Control Study

Variability of the lower limb symmetry index associated with the gait parameters in the overweight adult population with flatfoot: a case-control study

Background: Adult acquired flatfoot is characterized by a medial arch collapse during monopodal support in the stance phase, developing eversion of the calcaneus and abduction of the forefoot linked to the hindfoot. The purpose of our research was to analyze the dynamic symmetry index in the lower limbs comparing patients with flatfoot and normal foot. Methods: A case-control study was carried out with a sample of 62 participants divided into two groups consisting of 31 participants were overweight with bilateral flatfoot and 31 participants with healthy feet. A portable plantar pressure platform with piezoresistive sensors was used to measure the load symmetry index in the lower limbs in the foot areas and gait phases. Results: Gait pattern analysis showed statistically significant differences in the symmetry index for lateral load (p = 0.004), the initial contact phase (p = 0.025) and the forefoot phase (p < 0.001). Conclusion: The adults were overweight with bilateral flatfoot evidenced alterations in the symmetry index in the lateral load and in the initial contact and flatfoot contact phases, showing greater instability in overweight adult flatfoot compared to the people with normal feet.

Influence of the center of pressure on baropodometric gait pattern variations in the adult population with flatfoot: A case-control study

Background: Adult flatfoot is considered an alteration in the foot bone structure characterized by a decrease or collapse of the medial arch during static or dynamic balance in the gait pattern. The aim of our research was to analyze the center of pressure differences between the population with adult flatfoot and the population with normal feet. Methods: A case-control study involving 62 subjects was carried out on 31 adults with bilateral flatfoot and 31 healthy controls. The gait pattern analysis data were collected employing a complete portable baropodometric platform with piezoresistive sensors. Results: Gait pattern analysis showed statistically significant differences in the cases group, revealing lower levels in the left foot loading response of the stance phase in foot contact time (p = 0.016) and contact foot percentage (p = 0.019). Conclusion: The adult population with bilateral flatfoot evidenced higher contact time data in the total stance phase compared to the control group, which seems to be linked to the presence of foot deformity in the adult population.

A Deep Learning Method for Foot Progression Angle Detection in Plantar Pressure Images

Foot progression angle (FPA) analysis is one of the core methods to detect gait pathologies as basic information to prevent foot injury from excessive in-toeing and out-toeing. Deep learning-based object detection can assist in measuring the FPA through plantar pressure images. This study aims to establish a precision model for determining the FPA. The precision detection of FPA can provide information with in-toeing, out-toeing, and rearfoot kinematics to evaluate the effect of physical therapy programs on knee pain and knee osteoarthritis. We analyzed a total of 1424 plantar images with three different You Only Look Once (YOLO) networks: YOLO v3, v4, and v5x, to obtain a suitable model for FPA detection. YOLOv4 showed higher performance of the profile-box, with average precision in the left foot of 100.00% and the right foot of 99.78%, respectively. Besides, in detecting the foot angle-box, the ground-truth has similar results with YOLOv4 (5.58 ± 0.10° vs. 5.86 ± 0.09°, p = 0.013). In contrast, there was a significant difference in FPA between ground-truth vs. YOLOv3 (5.58 ± 0.10° vs. 6.07 ± 0.06°, p < 0.001), and ground-truth vs. YOLOv5x (5.58 ± 0.10° vs. 6.75 ± 0.06°, p < 0.001). This result implies that deep learning with YOLOv4 can enhance the detection of FPA.