Forefoot pathology in rheumatoid arthritis identified with ultrasound may not localise to areas of highest pressure: cohort observations at baseline and twelve months

BackgroundPlantar pressures are commonly used as clinical measures, especially to determine optimum foot orthotic design. In rheumatoid arthritis (RA) high plantar foot pressures have been linked to metatarsophalangeal (MTP) joint radiological erosion scores. However, the sensitivity of foot pressure measurement to soft tissue pathology within the foot is unknown. The aim of this study was to observe plantar foot pressures and forefoot soft tissue pathology in patients who have RA.Methods A total of 114 patients with established RA (1987 ACR criteria) and 50 healthy volunteers were assessed at baseline. All RA participants returned for reassessment at twelve months. Interface foot-shoe plantar pressures were recorded using an F-Scan® system. The presence of forefoot soft tissue pathology was assessed using a DIASUS musculoskeletal ultrasound (US) system. Chi-square analyses and independent t-tests were used to determine statistical differences between baseline and twelve months. Pearson’s correlation coefficient was used to determine interrelationships between soft tissue pathology and foot pressures.ResultsAt baseline, RA patients had a significantly higher peak foot pressures compared to healthy participants and peak pressures were located in the medial aspect of the forefoot in both groups. In contrast, RA participants had US detectable soft tissue pathology in the lateral aspect of the forefoot. Analysis of person specific data suggests that there are considerable variations over time with more than half the RA cohort having unstable presence of US detectable forefoot soft tissue pathology. Findings also indicated that, over time, changes in US detectable soft tissue pathology are out of phase with changes in foot-shoe interface pressures both temporally and spatially.Conclusions We found that US detectable forefoot soft tissue pathology may be unrelated to peak forefoot pressures and suggest that patients with RA may biomechanically adapt to soft tissue forefoot pathology. In addition, we have observed that, in patients with RA, interface foot-shoe pressures and the presence of US detectable forefoot pathology may vary substantially over time. This has implications for clinical strategies that aim to offload peak plantar pressures

Smart Footwear Insole for Recognition of Foot Pronation and Supination Using Neural Networks

Abnormal foot postures during gait are common sources of pain and pathologies of the lower limbs. Measurements of foot plantar pressures in both dynamic and static conditions can detect these abnormal foot postures and prevent possible pathologies. In this work, a plantar pressure measurement system is developed to identify areas with higher or lower pressure load. This system is composed of an embedded system placed in the insole and a user application. The instrumented insole consists of a low-power microcontroller, seven pressure sensors and a low-energy bluetooth module. The user application receives and shows the insole pressure information in real-time and, finally, provides information about the foot posture. In order to identify the different pressure states and obtain the final information of the study with greater accuracy, a Deep Learning neural network system has been integrated into the user application. The neural network can be trained using a stored dataset in order to obtain the classification results in real-time. Results prove that this system provides an accuracy over 90% using a training dataset of 3000+ steps from 6 different users.Ministerio de Economía y Competitividad TEC2016-77785-

Recent Innovations in Footwear and the Role of Smart Footwear in Healthcare—A Survey

© 2024 The Author(s). Licensee MDPI, Basel, Switzerland. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Smart shoes have ushered in a new era of personalised health monitoring and assistive technologies. Smart shoes leverage technologies such as Bluetooth for data collection and wireless transmission, and incorporate features such as GPS tracking, obstacle detection, and fitness tracking. As the 2010s unfolded, the smart shoe landscape diversified and advanced rapidly, driven by sensor technology enhancements and smartphones’ ubiquity. Shoes have begun incorporating accelerometers, gyroscopes, and pressure sensors, significantly improving the accuracy of data collection and enabling functionalities such as gait analysis. The healthcare sector has recognised the potential of smart shoes, leading to innovations such as shoes designed to monitor diabetic foot ulcers, track rehabilitation progress, and detect falls among older people, thus expanding their application beyond fitness into medical monitoring. This article provides an overview of the current state of smart shoe technology, highlighting the integration of advanced sensors for health monitoring, energy harvesting, assistive features for the visually impaired, and deep learning for data analysis. This study discusses the potential of smart footwear in medical applications, particularly for patients with diabetes, and the ongoing research in this field. Current footwear challenges are also discussed, including complex construction, poor fit, comfort, and high cost.Peer reviewe

GAIT PARTITIONING WITH SMART SOCKS SYSTEM

Gait is a very complex movement, involving the central nervous system and a significant part of the skeletomuscular system. Any disease that is affecting one or more of the involved parts will reflect in the gait. Therefore, gait analysis has been studied extensively in the context of early disease diagnostics, post-operation rehabilitation monitoring, and sports injury prevention. Gait cycle phase partitioning is one of the most common gait characteristic analysis methods, which utilizes the cyclical nature of human gait. Pressure sensitive mats and insoles are considered the gold standard, but some inherent limitations of these methods urge researchers to seek for alternatives. One of the proposed alternatives is Smart Sock systems, which contain textile pressure sensors. The main limitation of Smart Sock systems is the limited number of sensors, thus complicating gait phase partitioning by these systems. The present paper describes gait phase partitioning using plantar pressure signal obtained by a Smart Sock system. Six-phase partitioning was achieved, including such gait phases as initial contact, loading response, mid stance, terminal stance, pre-swing and swing phase. Mean gait cycle time values obtained from the experimental data were in accordance with the ones found in the literature.

Wireless Pressure Measurement and Power Generation Using Sensor

This paper has implemented and designed for measurement of pressure using wireless and applied it for our day-to-day power requirements. The pressure acts between the skin surface and its supporting surface that humans experience during daily activities. Here, we prefer sensors to measure the pressure, voltage and angle. Piezoelectric sensors are used for measure the pressure & voltage through LCD. Micro-Electro Mechanical Sensor (MEMS) is used to measure the speed from the 3D angle values. The Controller is developed to interface the Micro-electromechanical (MEMS) sensors and piezoelectric sensors that have been designed for analysis the pressure and get power during the body movement. By using the zigbee module, the analyzed pressure is transmitted and stored in the PC. The great advantage of this project is that it doesn’t require any external power supply. Using the DC-DC booster it can increase the generated voltage and stored in battery. It provides power supply for this device and some electronic applications. Such device provides low power consumption, convenient and comfortable testing system

Biomechanical Effects of Prefabricated Foot Orthoses and Rocker-Sole Footwear in Individuals with First Metatarsophalangeal Joint Osteoarthritis

OBJECTIVE: To evaluate the effects of prefabricated foot orthoses and rocker-sole footwear on spatiotemporal parameters, hip and knee kinematics, and plantar pressures in people with first metatarsophalangeal (MTP) joint osteoarthritis (OA). METHODS: A total of 102 people with first MTP joint OA were randomly allocated to receive prefabricated foot orthoses or rocker-sole footwear. The immediate biomechanical effects of the interventions (compared to usual footwear) were examined using a wearable sensor motion analysis system and an in-shoe plantar pressure measurement system. RESULTS: Spatiotemporal/kinematic and plantar pressure data were available from 88 and 87 participants, respectively. The orthoses had minimal effect on spatiotemporal or kinematic parameters, while the rocker-sole footwear resulted in reduced cadence, percentage of the gait cycle spent in stance phase, and sagittal plane hip range of motion. The orthoses increased peak pressure under the midfoot and lesser toes. Both interventions significantly reduced peak pressure under the first MTP joint, and the rocker-sole shoes also reduced peak pressure under the second through fifth MTP joints and heel. When the effects of the orthoses and rocker-sole shoes were directly compared, there was no difference in peak pressure under the hallux, first MTP joint, or heel; however, the rocker-sole shoes exhibited lower peak pressure under the lesser toes, second through fifth MTP joints, and midfoot. CONCLUSION: Prefabricated foot orthoses and rocker-sole footwear are effective at reducing peak pressure under the first MTP joint in people with first MTP joint OA, but achieve this through different mechanisms. Further research is required to determine whether these biomechanical changes result in improvements in symptoms