: Parkinson’s disease (PD) is a progressive neurodegenerative disorder. Gait impairments are common among people with PD. Wearable sensor systems can be used for gait analysis by providing spatio-temporal parameters useful to investigate the progression of gait problems in Parkinson disease. However, various methods and tools with very high variability have been developed. The aim of this study is to review published articles of the last 10 years (from 2008 to 2018) concerning the application of wearable sensors to assess spatio-temporal parameters of gait in patients with PD. We focus on inertial sensors used for gait analysis in the clinical environment (i.e., we do not cover the use of inertial sensors to monitor walking or general activities at home, in unsupervised environments). Materials and Methods: Relevant articles were searched in the Medline database using Pubmed. Results and Discussion: Two hundred ninety-four articles were initially identified while searching the scientific literature regarding this topic. Thirty-six articles were selected and included in this review. Conclusion: Wearable motion sensors are useful, non-invasive, low-cost, and objective tools that are being extensively used to perform gait analysis on PD patients. Being able to diagnose and monitor the progression of PD patients makes wearable sensors very useful to evaluate clinical efficacy before and after therapeutic interventions. However, there is no uniformity in the use of wearable sensors in terms of: number of sensors, positioning, chosen parameters, and other characteristics. Future research should focus on standardizing the measurement setup and selecting which spatio-temporal parameters are the most informative to analyze gait in PD. These parameters should be provided as standard assessments in all studies to increase replicability and comparability of results.

New treatments based on peripheral stimulation of the sensory-motor system have shown to be promising in rehabilitation strategies for patients with neurological disorders, including Parkinson’s disease (PD), especially in regards to reducing gait impairment, and hence, the incidence of falls. The aim of this study was to evaluate the change in several gait parameters measured by sensor inertial measurement in PD patients after acute plantar stimulation, under the distal phalanx of the big toe, and underneath the head of the first metatarsal joint of both feet, using a 3D printing insole. In order to assess whether the effects are selective for PD patients, we compared the effect of the treatment in a control group (age-matched) consisting of patients with other neurological disorders which also displayed gait and balance impairment, and a similar cognitive function, depressive symptoms, body mass index, and comorbidity burden observed in the PD group. Plantar foot stimulation in PD patients eliminated the significant (p < 0.05) alterations existing in stride asymmetry and in stride variability. When comparing the effects of post-plantar stimulation with the respective basal level, considered as 100% in both groups, we observed a significant (p = 0.019, Mann–Whitney test) increase in stride length compared to basal in the PD group and control group. No significant effects of foot plantar stimulation were observed in any of the gait parameters in the control group. Plantar foot stimulation has a positive effect on the step and stride length, and has a positive effect on walking stability, measured by the increase in stride length. No significant effect was observed on bradykinesia because it did not improve walking velocity. These findings indicate that foot plantar stimulation using a 3D printing insole seems to generate a more stable walking pattern in PD patients, with an interesting applicability, and a low-cost, for reducing gait impairment in PD patients.

Background: In clinical practice, specific customization is needed to address foot pathology, which must be disease and patient-specific. To date, the traditional methods for manufacturing custom functional Foot Orthoses (FO) are based on plaster casting and manual manufacturing, hence orthotic therapy depends entirely on the skills and expertise of individual practitioners. This makes the procedures difficult to standardize and replicate, as well as expensive, time-consuming and material-wasting, as well as difficult to standardize and replicate. 3D printing offers new perspectives in the development of patient-specific orthoses, as it permits addressing all the limitations of currently available technologies, but has been so far scarcely explored for the podiatric field, so many aspects remain unmet, especially for what regards customization, which requires the definition of a protocol that entails all stages from patient scanning to manufacturing. Methods: A feasibility study was carried out involving interdisciplinary cooperation between industrial engineers and podiatrists. To that end: (i) For patient-specific data acquisition, 3D scanning of the foot is compared to traditional casting. (ii) a modelling GD workflow is first created to design a process permitting easy creations of customized shapes, enabling the end user (the podiatrist) to interactively customize the orthoses. Then, (iii) a comparison is made between different printing materials, in order to reproduce the same mechanical behavior shown by standard orthoses. To do this, the mechanical properties of standard materials (Polycarbonate sheets), cut and hand-shaped, are compared with four groups of 3D printed samples: poly(ethylene glycol) (PETG), poly(acrylonitrile-butadiene.styrene) (ABS), polycarbonate (PC) and poly(lactic acid) (PLA) obtained by Fused Filament Fabrication (FFF). Results: Differences found between the foot plaster model obtained with the plaster slipper cast in a neutral position and the model of the real foot obtained with 3D scanning in the same position can be ascribed to the non-stationarity of the patient during the acquisition process, and were limited by a locking system with which no substantial differences in the almost entire sole of the foot scan were observed. Conclusions: Using the designed GD workflow, podiatrists with limited CAD skills can easily design and interactively customize foot orthoses to adapt them to the patients’ clinical needs. 3D printing enables the complex shape of the orthoses to be reproduced easily and quickly. Compared to Polycarbonate sheets (gold standard), all the printed materials were less deformable and reached lower yield stress for comparable deformation. No modifications in any of the materials as a result of printing process were observed.

Background: Diabetic peripheral neuropathy (DPN) is known to predict foot ulceration, lower-extremity amputation and mortality. Patients with diabetes mellitus have a predisposition toward developing chronic inflammatory demyelinating polyneuropathy, and this may also facilitate the formation of diabetic foot and cutaneous impairment, which are considered one of the most serious impairments of diabetes mellitus, with a prevalence of 4–10% in this population. Biomarkers research provides opportunities for the early diagnosis of these complications for specific treatments useful to prevent amputation and, therefore, physical inability and mental disturbance. The recent literature has suggested that glycemic levels may be a novel factor in the pathogenesis of diabetic foot complications and is an important mediator of axonal dysfunction. The aim of this systematic literary review is to determine whether hemoglobin A1c (HbA1c) is a positive predictor for diabetic foot peripheral neuropathy and its complications, such as foot cutaneous impairments. There is a lack of consensus regarding the effect of glycemic variability on diabetic foot peripheral neuropathy, unlike other complications such as retinopathy, nephropathy or micro/macrovascular pathology Methods: Relevant articles were searched in the Medline database using PubMed and Scopus and relevant keywords. The primary search terms used were “glycated hemoglobin” OR “HbA1c” AND “diabetic neuropathies” AND “Foot”. Results: A number of articles (336) were initially identified while searching the scientific literature regarding this topic, and 32 articles were selected and included in this review. Conclusions: This review highlights the role of HbA1c in diabetic foot peripheral neuropathy. Biomarkers play an important role in the decision-making process, and HbA1c levels are extensively used for diabetic foot clinical outcomes and settings, but biomarker research in diabetic foot peripheral neuropathy is in its infancy and will require careful attention to a number of factors and associations, since the consequences of DPN also include neurological alterations. HbA1c is an accurate and easy-to-administer test and can be an effective biomarker in establishing the diagnosis of diabetes, but future research should focus on standardizing the HbA1c level and selecting which DPN value and its correlated complications, such as foot cutaneous impairments, are the most informative.

Background and Objectives: Diabetes mellitus is considered a serious public health problem due to its high prevalence and related complications, including gait and posture impairments due to neuropathy and vascular alterations and the subsequent increased risk of falls. The gait of patients with diabetes is characterized by alterations of the main spatiotemporal gait parameters such as gait velocity, cadence, stride time and length, which are also known to worsen with disease course. Wearable sensor systems can be used for gait analysis by providing spatiotemporal parameters and postural control (evaluated from the perspective of body sway), useful for investigating the disease progression. Thanks to their small size and low cost of their components, inertial measurement units (IMUs) are easy to wear and are cheap tools for movement analysis. Materials and Methods: The aim of this study is to review articles published in the last 21 years (from 2000 to 2021) concerning the application of wearable sensors to assess spatiotemporal parameters of gait and body postural alterations in patients with diabetes mellitus. Relevant articles were searched in the Medline database using PubMed, Ovid and Cochrane libraries. Results: One hundred and four articles were initially identified while searching the scientific literature on this topic. Thirteen were selected and analysed in this review. Wearable motion sensors are useful, noninvasive, low-cost, and objective tools for performing gait and posture analysis in diabetic patients. The IMUs can be worn at the lumber levels, tibias or feet, and different spatiotemporal parameters of movement and static posture can be assessed. Conclusions: Future research should focus on standardizing the measurement setup and selecting the most informative spatiotemporal parameters for gait and posture analysis.