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IntroductionThe prevalence of diabetes mellitus in the United Arab Emirates stands significantly high. Considering the etiopathogenesis for diabetic foot ulcers, studies suggest that increased plantar pressure, also referred to as the peak plantar pressure beyond a threshold value leads to the breakdown of skin and thus causes an ulcer. The accurate analysis of ground reaction force and peak plantar pressure could be suggestive and predictive for the occurrence of foot ulceration among diabetes mellitus and the study aims to analyze the kinetics at the ankle joint among diabetics in the UAE.MethodologyThe cross-sectional study was conducted at the Thumbay Physical Therapy and Rehabilitation Hospital, Gulf Medical University, Ajman, United Arab Emirates. 38 out of a total of 120 participants screened and diagnosed with Type 2 diabetes mellitus were taken for data collection and analysis. BTS motion analysis and Wintrack foot scan mat were used for kinetics at the ankle joint.ResultsHigher mean peaks of plantar pressure, 810, 654, and 911 kPa respectively were found at all three phases of the gait cycle. A positive and high correlation was found between peak plantar pressure risk of foot ulcer (r= 0.84). A negative and moderate correlation was observed for ankle joint moment and power.ConclusionThe diabetic population in the United Arab Emirates could be at higher risk of foot ulceration with significantly increased peak plantar pressure. The altered kinetics such as reduced ankle joint moment and power could further add to the risk.
IntroductionThe prevalence of diabetes mellitus in the United Arab Emirates stands significantly high. Considering the etiopathogenesis for diabetic foot ulcers, studies suggest that increased plantar pressure, also referred to as the peak plantar pressure beyond a threshold value leads to the breakdown of skin and thus causes an ulcer. The accurate analysis of ground reaction force and peak plantar pressure could be suggestive and predictive for the occurrence of foot ulceration among diabetes mellitus and the study aims to analyze the kinetics at the ankle joint among diabetics in the UAE.MethodologyThe cross-sectional study was conducted at the Thumbay Physical Therapy and Rehabilitation Hospital, Gulf Medical University, Ajman, United Arab Emirates. 38 out of a total of 120 participants screened and diagnosed with Type 2 diabetes mellitus were taken for data collection and analysis. BTS motion analysis and Wintrack foot scan mat were used for kinetics at the ankle joint.ResultsHigher mean peaks of plantar pressure, 810, 654, and 911 kPa respectively were found at all three phases of the gait cycle. A positive and high correlation was found between peak plantar pressure risk of foot ulcer (r= 0.84). A negative and moderate correlation was observed for ankle joint moment and power.ConclusionThe diabetic population in the United Arab Emirates could be at higher risk of foot ulceration with significantly increased peak plantar pressure. The altered kinetics such as reduced ankle joint moment and power could further add to the risk.
<b>Introduction</b>: Patients with diabetes are more likely to fall due to increased plantar pressure and decreased strength in the lower extremities.<br /> <b>Objectives:</b> To determine the influence of isometric ankle strength on dynamic foot plantar pressure in diabetes and non-diabetes participants.<br /> <b>Methods: </b>Twenty diabetes patients and twenty non-diabetes participants with age 28-54 years, height 150-182 cm, weight 48-90 kg, and BMI 25-54 kg/m<sup>2</sup> participated in the study. The diabetes level was determined based on fasting plasma glucose levels. The resisted isometric muscle strength of the foot during dorsiflexion, plantar flexion, inversion, and eversion was measured using an electronic handheld dynamometer. The plantar pressure distribution during dynamic conditions was determined by using a 48.7×44.7 cm pressure platform. The outcome measures between diabetes and non-diabetes groups were statistically compared by student t-test. The correlation coefficient was determined by the Pearson correlation coefficient test. A p-value of less than 0.05 was considered significant.<br /> <b>Result: </b>The significant differences were found between diabetes and non-diabetes participants for the dorsiflexion (p=.048), plantarflexion (p=.031), inversion (p=.011), eversion (p=.024), peak pressure (p=.024), pressure per square inch (p=.012), pressure time integral (p=.014), and peak pressure gradient (p=.009). Significant relationships between resisted isometric ankle joint strength and foot plantar pressure for diabetes patients and non-diabetes participants were found.<br /> <b>Conclusion: </b>The present study’s findings reflect the higher frequency of plantar pressure distribution and higher muscle weakness in diabetes patients than in non-diabetes participants. These findings suggested that pressure data could help us to customize therapy strategies for patients with diabetes and prescribe a proper exercise intervention’s short-and long-term effects on gait biomechanics.
Diabetes is a significant global health issue impacting millions. Approximately 26 million diabetics experience foot ulcers, with 20% ending up with amputations, resulting in high morbidity, mortality, and costs. Plantar pressure screening shows potential for early detection of Diabetic Foot Ulcers (DFUs). Although foot ulcers often occur due to excessive pressure on the soles during dynamic activities, most studies focus on static pressure measurements. This study’s primary objective is to apply wireless plantar pressure sensor-embedded insoles to classify and detect diabetic feet from healthy ones based on dynamic plantar pressure. The secondary objective is to compare statistical-based and Machine Learning (ML) classification methods. Data from 150 subjects were collected from the insoles during walking, revealing that diabetic feet have higher plantar pressure than healthy feet, which is consistent with prior research. The Adaptive Boosting (AdaBoost) ML model achieved the highest accuracy of 0.85, outperforming the statistical method, which had an accuracy of 0.67. These findings suggest that ML models, combined with pressure sensor-embedded insoles, can effectively classify healthy and diabetic feet using plantar pressure features. Future research will focus on using these insoles with ML to classify various stages of diabetic neuropathy, aiming for early prediction of foot ulcers in home settings.
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