Gait alterations in the UAE population with and without diabetic complications using both traditional and entropy measures

A Scoping Review of Wearable Technologies for Use in Individuals With Intellectual Disabilities and Diabetic Peripheral Neuropathy

BACKGROUND

Individuals with intellectual disabilities (IDs) are at risk of diabetes mellitus (DM) and diabetic peripheral neuropathy (DPN), which can lead to foot ulcers and lower-extremity amputations. However, cognitive differences and communication barriers may impede some methods for screening and prevention of DPN. Wearable and mobile technologies-such as smartphone apps and pressure-sensitive insoles-could help to offset these barriers, yet little is known about the effectiveness of these technologies among individuals with ID.

METHODS

We conducted a scoping review of the databases Embase, PubMed, and Web of Science using search terms for DM, DPN, ID, and technology to diagnose or monitor DPN. Finding a lack of research in this area, we broadened our search terms to include any literature on technology to diagnose or monitor DPN and then applied these findings within the context of ID.

RESULTS

We identified 88 articles; 43 of 88 (48.9%) articles were concerned with gait mechanics or foot pressures. No articles explicitly included individuals with ID as the target population, although three articles involved individuals with other cognitive impairments (two among patients with a history of stroke, one among patients with hemodialysis-related cognitive changes).

CONCLUSIONS

Individuals with ID are not represented in studies using technology to diagnose or monitor DPN. This is a concern given the risk of DM complications among patients with ID and the potential for added benefit of such technologies to reduce barriers to screening and prevention. More studies should investigate how wearable devices can be used among patients with ID.

Gait Analysis, Metabolic Parameters and Adherence to the Mediterranean Diet in Patients with Type 2 Diabetes Mellitus Compared with Healthy Controls: A Pilot Study

BACKGROUND AND PURPOSE

Patients with type 2 diabetes mellitus (T2DM) are prone to developing diabetic peripheral neuropathy (DPN) with an increased risk of injuries while walking, potentially leading to plantar ulcers. We aimed to assess the early gait changes in T2DM patients without clinical signs of DPN in comparison to age-matched healthy controls (HC).

SUBJECTS AND METHODS

One hundred T2DM patients (78 women, mean age: 66.4 ± 11.5 years) and 50 age-matched HC (34 women, mean age 62.1 ± 7.9 years) were evaluated with the PODOSmart® gait analysis device. Anthropometric and biochemical data, as well as dietary habits were collected for all participants. T2DM patients also completed the Diabetes Distress (DS) self-report validated questionnaire.

RESULTS

One patient was excluded from the study due to lack of recent biochemical data. Among the T2DM patients, 88.9% reported little or no DS and 11.1% moderate DS. The T2DM group had higher body mass index, waist circumference, systolic blood pressure, glycated hemoglobin A1c, sodium, white blood cell count, triglycerides and low-density lipoprotein cholesterol, but lower high-density lipoprotein cholesterol than HC (p < 0.05 for all comparisons). The MedDiet score was satisfactory in both groups (p > 0.05). Significant differences were found between the two study groups in gaitline heel off, propulsion speed, foot progression angle, time taligrade phase, stride length, walking speed, angle attack, oscillation speed, pronation-supination toe off and clearance.

CONCLUSIONS

The T2DM patients without self-reported DS or clinical signs of DPN may exhibit significant differences in several gait parameters analyzed with PODOSmart®. Whether gait analysis can be used as an early diagnostic tool of T2DM complications should be further explored.

Plantar pressure alterations associated with increased BMI in young adults

BACKGROUND

Despite evidence suggesting that excess weight is linked to gait alterations and foot disorders, its effect on peak plantar pressure (PPP) variability and complexity during walking remains poorly understood.

RESEARCH QUESTION

This study aimed to examine the influence of overweight (BMI ≥ 25) on the dynamic PPP distribution during gait using traditional and nonlinear dynamic measures in young college students.

METHODS

Fifty-two overweight (BMI >25, average 29.3 ± 4.02) and sixty-four control college students (BMI<25, 21.7 ± 1.76) aged 18-25 years, walked across a Tekscan gait assessment system at their preferred speed. A t-test or a Mann Whitney U test was used for analysis, subject to data normality. Kinematic, kinetic, spatiotemporal, and GaitEn (sample entropy of 2D spatial PPP maps) for window lengths (m=2) at various filtering levels (r) were used to explore the impact of BMI on PPP alterations.

RESULTS AND SIGNIFICANCE

The overweight group exhibited significantly higher mean PPP. The PPP under the forefoot region was also significantly higher for the overweight group as compared to the heel. The mean GaitEn values of overweight and control groups were found significantly different at r = (0.7-0.8) x STD, where GaitEn of the control group was relatively higher, which indicates better gait performance as compared to the overweight group in alignment with previous studies. A significant correlation of GaitEn with STD of PPP was revealed for the overweight group only, suggesting that overweight could significantly change the regularity or the complexity of the PPP series. Although no spatiotemporal parameters (stride length, step length, step width) were significantly affected by the increased BMI, GaitEn dynamic measure, along with spatiotemporal (decrease in gait velocity and cadence with increased BMI), and kinetic measures (increased maximum forces and plantar pressure with increased BMI), were significantly affected by overweight, indicating the feasibility of assessing the impact of increased BMI using pressure platforms in clinical settings.

Gait analysis under the lens of statistical physics

Human gait is a fundamental activity, essential for the survival of the individual, and an emergent property of the interactions between complex physical and cognitive processes. Gait is altered in many situations, due both to external constraints, as e.g. paced walk, and to physical and neurological pathologies. Its study is therefore important as a way of improving the quality of life of patients, but also as a door to understanding the inner working of the human nervous system. In this review we explore how four statistical physics concepts have been used to characterise normal and pathological gait: entropy, maximum Lyapunov exponent, multi-fractal analysis and irreversibility. Beyond some basic definitions, we present the main results that have been obtained in this field, as well as a discussion of the main limitations researchers have dealt and will have to deal with. We finally conclude with some biomedical considerations and avenues for further development.

Gait Parameters and Peripheral Neuropathy in Patients With Diabetes: A Meta-Analysis

OBJECTIVE

To investigate the relationship between diabetic peripheral neuropathy (DPN) and gait abnormality in diabetic patients.

METHODS

Related research concerning the gait of diabetic patients with and without DPN was collected and analyzed by searching PubMed, Embase, and Web of Science. Statistical analysis was performed by using RevMan 5.3 software.

RESULTS

Twenty-one studies were included in this meta-analysis, consisting of 499 diabetic neuropathy patients and 467 diabetes controls without neuropathy. Meta-analysis results showed lower gait velocity, shorter stride length, longer stride time, longer stance time, and higher maximum knee extension moment in the DPN group, compared with their counterparts.

CONCLUSION

Among diabetic patients, those complicated with DPN possess lower gait velocity, shorter stride length, longer stride time, longer stance time, and higher maximum knee extension moment.

Single Sensor Gait Analysis to Detect Diabetic Peripheral Neuropathy: A Proof of Principle Study

This study explored the potential utility of gait analysis using a single sensor unit (inertial measurement unit [IMU]) as a simple tool to detect peripheral neuropathy in people with diabetes. Seventeen people (14 men) aged 63±9 years (mean±SD) with diabetic peripheral neuropathy performed a 10-m walk test instrumented with an IMU on the lower back. Compared to a reference healthy control data set (matched by gender, age, and body mass index) both spatiotemporal and gait control variables were different between groups, with walking speed, step time, and SDa (gait control parameter) demonstrating good discriminatory power (receiver operating characteristic area under the curve >0.8). These results provide a proof of principle of this relatively simple approach which, when applied in clinical practice, can detect a signal from those with known diabetes peripheral neuropathy. The technology has the potential to be used both routinely in the clinic and for tele-health applications. Further research should focus on investigating its efficacy as an early indicator of or effectiveness of the management of peripheral neuropathy. This could support the development of interventions to prevent complications such as foot ulceration or Charcot's foot.