Patient and Provider Perspective of Smart Wearable Technology in Diabetic Foot Ulcer Prevention: A Systematic Review

The experience and perception of wearable devices in Parkinson's disease patients: a systematic review and meta-synthesis of qualitative studies

BACKGROUND

Parkinson's disease (PD) is the fastest-growing neurodegenerative disorder, affecting over 8.5 million people worldwide, with symptoms that severely impact patients' quality of life. While treatments like levodopa and deep brain stimulation help manage symptoms, they require frequent adjustments and have limitations. Wearable devices offer real-time monitoring of motor and non-motor symptoms, enabling personalized treatment, but challenges related to comfort, usability, and patient adherence hinder their widespread adoption. Many individuals with PD experience discomfort, emotional distress, or interface difficulties, reducing long-term adherence. This study synthesizes qualitative research on patients' experiences with wearables to identify key usability barriers and improve device design for better clinical integration.

METHODS

Following the Joanna Briggs Institute methodology for qualitative systematic reviews, we searched PubMed, Web of Science, Embase, Cochrane Library, CINAHL, CNKI, WanFang, and VIP databases up to March 3, 2025. Additional gray literature and reference lists were examined manually. Included qualitative studies underwent comprehensive assessment, integration, and analysis.

RESULTS

Nine studies were included, identifying four main themes and eleven sub-themes. The four primary themes were physiological experience, psychological Responses, social Interaction, and Expectation.

CONCLUSION

This meta-synthesis reveals the dual role of wearable devices in managing Parkinson's disease, improving patient autonomy and disease control while presenting challenges in comfort, reliability, and emotional well-being. The findings emphasize the need for personalized, context-sensitive devices that adapt to fluctuating PD symptoms, address privacy concerns, and seamlessly integrate into clinical practice to improve clinical outcomes and patient adherence.

Developing a Smart Sensing Sock to Prevent Diabetic Foot Ulcers: Qualitative Focus Group and Interview Study

BACKGROUND

Diabetic foot ulcers are common and costly. Most cases are preventable, although few interventions exist to reliably support patients in performing self-care. Emerging technologies are showing promise in this domain, although patient and health care provider perspectives are rarely incorporated into digital intervention designs.

OBJECTIVE

This study explored patient and health care provider feedback on a smart sensing sock to detect shear strain and alert the wearer to change their behavior (ie, pause activity and check their feet) and considered how patient experience and attitudes toward self-care are likely to impact uptake and long-term effective engagement with the device to curate guiding principles for successful future intervention development.

METHODS

This qualitative study combined semistructured interviews and a focus group alongside a participant advisory group that was consulted throughout the study. In total, 20 people with diabetic neuropathy (n=16, 80% with history of diabetic foot ulcers) and 2 carers were recruited directly from podiatry clinics as well as via a recruitment network and national health mobile app for one-to-one interviews either in person or via landline or video call. A total of 6 podiatrists were recruited via professional networks for 1 virtual focus group. Participants were asked about their experience of diabetic foot health and for feedback on the proposed device, including how it might work for them in daily life or clinical practice. The data were analyzed thematically.

RESULTS

Three main themes were generated, each raising a barrier to the use of the sock complemented by potential solutions: (1) patient buy-in-challenged by lack of awareness of risk and potentially addressed through using the device to collect and record evidence to enhance clinical messaging; (2) effective engagement-challenged by difficulties accepting and actioning information and requiring simple, specific, and supportive instructions in line with podiatrist advice; and (3) sustained use-challenged by difficulties coping, with the possibility to gain control through an early warning system.

CONCLUSIONS

While both patients and podiatrists were interested in the concept, it would need to be packaged as part of a wider health intervention to overcome barriers to uptake and longer-term effective engagement. This study recommends specific considerations for the framing of feedback messages and instructions as well as provision of support for health care providers to integrate the use of such smart devices into practice. The guiding principles generated by this study can orient future research and development of smart sensing devices for diabetic foot care to help optimize patient engagement and improve health outcomes.

An Overview on Diabetic Neuropathy

The term "Diabetic neuropathy" refers to a collection of clinical and subclinical symptoms caused by problems with the peripheral nervous system. Diabetes, which affects approximately 381 million people worldwide, is the source of dysfunction due to the emergence of microvascular complications. It is anticipated that in the next ten years, Diabetic neuropathy will manifest in about 50% of patients who are currently diagnosed with diabetes. Clinical diagnosis can be established by getting a thorough patient history and exploring the symptoms to rule out alternative causes. Although distal symmetrical polyneuropathy, or just, is the most common and well-researched variant of the disorder, this review will concentrate on it. The multifactorial pathogenesis is linked to various inflammatory, vascular, metabolic, and neurodegenerative illnesses. The three fundamental molecular alterations that lead to the development of diabetic neuropathic pain are oxidative stress, endothelial dysfunction, and chronic inflammation. These three elements are crucial in the development of polyneuropathy because their combination might result in direct axonal damage and nerve ischemia. The purpose of this article was to provide a narrative review of diabetic neuropathy. We provide an overview of the most recent data on biomarkers, the pathogenesis of the illness, the most recent epidemiology of diabetic neuropathy, and the existing screening and diagnosis outcome measures used in both clinical and research contexts.

Personalized and predictive strategies for diabetic foot ulcer prevention and therapeutic management: potential improvements through introducing Artificial Intelligence and wearable technology

Diabetic foot ulcers represent a serious and costly complication of diabetes, with significant morbidity and mortality. The purpose of this study was to explore advancements in Artificial Intelligence, and wearable technologies for the prevention and management of diabetic foot ulcers. Key findings indicate that Artificial Intelligence-driven predictive analytics can identify early signs of diabetic foot ulcers, enabling timely interventions. Wearable technologies, such as continuous glucose monitors, smart insoles, and temperature sensors, provide real-time monitoring and early warnings. These technologies promise to revolutionize diabetic foot ulcer prevention by offering personalized care plans and fostering a participatory healthcare model. However, the review also highlights challenges such as patient adherence, socioeconomic barriers, and the need for further research to validate these technologies' effectiveness. The integration of artificial intelligence and wearable technologies holds the potential to significantly improve diabetic foot ulcer outcomes, reduce healthcare costs, and provide a more proactive and personalized approach to diabetic care. Further investments in digital infrastructure, healthcare provider training, and addressing ethical considerations are essential for successful implementation.

Integrating bioinformatics and multiple machine learning to identify mitophagy-related targets for the diagnosis and treatment of diabetic foot ulcers: evidence from transcriptome analysis and drug docking

Background

Diabetic foot ulcers are the most common and serious complication of diabetes mellitus, the high morbidity, mortality, and disability of which greatly diminish the quality of life of patients and impose a heavy socioeconomic burden. Thus, it is urgent to identify potential biomarkers and targeted drugs for diabetic foot ulcers.

Methods

In this study, we downloaded datasets related to diabetic foot ulcers from gene expression omnibus. Dysregulation of mitophagy-related genes was identified by differential analysis and weighted gene co-expression network analysis. Multiple machine algorithms were utilized to identify hub mitophagy-related genes, and a novel artificial neural network model for assisting in the diagnosis of diabetic foot ulcers was constructed based on their transcriptome expression patterns. Finally, potential drugs that can target hub mitophagy-related genes were identified using the Enrichr platform and molecular docking methods.

Results

In this study, we identified 702 differentially expressed genes related to diabetic foot ulcers, and enrichment analysis showed that these genes were associated with mitochondria and energy metabolism. Subsequently, we identified hexokinase-2, small ribosomal subunit protein us3, and l-lactate dehydrogenase A chain as hub mitophagy-related genes of diabetic foot ulcers using multiple machine learning algorithms and validated their diagnostic performance in a validation cohort independent of the present study (The areas under roc curve of hexokinase-2, small ribosomal subunit protein us3, and l-lactate dehydrogenase A chain are 0.671, 0.870, and 0.739, respectively). Next, we constructed a novel artificial neural network model for the molecular diagnosis of diabetic foot ulcers, and the diagnostic performance of the training cohort and validation cohort was good, with areas under roc curve of 0.924 and 0.840, respectively. Finally, we identified retinoic acid and estradiol as promising anti-diabetic foot ulcers by targeting hexokinase-2 (-6.6 and -7.2 kcal/mol), small ribosomal subunit protein us3 (-7.5 and -8.3 kcal/mol), and l-lactate dehydrogenase A chain (-7.6 and -8.5 kcal/mol).

Conclusion

The present study identified hexokinase-2, small ribosomal subunit protein us3 and l-lactate dehydrogenase A chain, and emphasized their critical roles in the diagnosis and treatment of diabetic foot ulcers through multiple dimensions, providing promising diagnostic biomarkers and targeted drugs for diabetic foot ulcers.

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

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.

Development of novel lysosome-related signatures and their potential target drugs based on bulk RNA-seq and scRNA-seq for diabetic foot ulcers

BACKGROUND

Diabetic foot ulcers (DFU) is the most serious complication of diabetes mellitus, which has become a global health problem due to its high morbidity and disability rates and the poor efficacy of conventional treatments. Thus, it is urgent to identify novel molecular targets to improve the prognosis and reduce disability rate in DFU patients.

RESULTS

In the present study, bulk RNA-seq and scRNA-seq associated with DFU were downloaded from the GEO database. We identified 1393 DFU-related DEGs by differential analysis and WGCNA analysis together, and GO/KEGG analysis showed that these genes were associated with lysosomal and immune/inflammatory responses. Immediately thereafter, we identified CLU, RABGEF1 and ENPEP as DLGs for DFU using three machine learning algorithms (Randomforest, SVM-RFE and LASSO) and validated their diagnostic performance in a validation cohort independent of this study. Subsequently, we constructed a novel artificial neural network model for molecular diagnosis of DFU based on DLGs, and the diagnostic performance in the training and validation cohorts was sound. In single-cell sequencing, the heterogeneous expression of DLGs also provided favorable evidence for them to be potential diagnostic targets. In addition, the results of immune infiltration analysis showed that the abundance of mainstream immune cells, including B/T cells, was down-regulated in DFUs and significantly correlated with the expression of DLGs. Finally, we found latamoxef, parthenolide, meclofenoxate, and lomustine to be promising anti-DFU drugs by targeting DLGs.

CONCLUSIONS

CLU, RABGEF1 and ENPEP can be used as novel lysosomal molecular signatures of DFU, and by targeting them, latamoxef, parthenolide, meclofenoxate and lomustine were identified as promising anti-DFU drugs. The present study provides new perspectives for the diagnosis and treatment of DFU and for improving the prognosis of DFU patients.

Stepping Forward: A Scoping Systematic Literature Review on the Health Outcomes of Smart Sensor Technologies for Diabetic Foot Ulcers

Diabetic foot ulcers (DFUs) pose a significant challenge in diabetes care, demanding advanced approaches for effective prevention and management. Smart insoles using sensor technology have emerged as promising tools to address the challenges associated with DFU and neuropathy. By recognizing the pivotal role of smart insoles in successful prevention and healthcare management, this scoping review aims to present a comprehensive overview of the existing evidence regarding DFU studies related to smart insoles, offloading sensors, and actuator technologies. This systematic review identified and critically evaluated 11 key studies exploring both sensor technologies and offloading devices in the context of DFU care through searches in CINAHL, MEDLINE, and ScienceDirect databases. Predominantly, smart insoles, mobile applications, and wearable technologies were frequently utilized for interventions and patient monitoring in diabetic foot care. Patients emphasized the importance of these technologies in facilitating care management. The pivotal role of offloading devices is underscored by the majority of the studies exhibiting increased efficient monitoring, prevention, prognosis, healing rate, and patient adherence. The findings indicate that, overall, smart insoles and digital technologies are perceived as acceptable, feasible, and beneficial in meeting the specific needs of DFU patients. By acknowledging the promising outcomes, the present scoping review suggests smart technologies can potentially redefine DFU management by emphasizing accessibility, efficacy, and patient centricity.

The quest for wellness: How to optimise self-care strategies for diabetic foot management?

Diabetic foot ulceration (DFU) is common and highly recurrent, negatively impacting the individuals' quality of life. The 2023 guidelines of the International Working Group on the Diabetic Foot emphasise that adherence to foot self-care recommendations is one of the most important factors in DFU prevention. These guidelines also briefly mention that depression and other psychosocial problems can hamper treatment and ulcer healing. Moreover, a new clinical question was added on psychological interventions for ulcer prevention, although the evidence regarding the role of psychological and social factors is still limited. To help the field progress, this narrative overview discusses how a stronger focus on psychological factors by both researchers and clinicians could improve the care for people at high DFU risk. The review starts with a testimony of a person living with DFU, explaining that for him, the absence of shared decision-making has been a key barrier to successful foot self-care implementation. Intervention studies that address patient-reported barriers are still scarce, and are therefore urgently needed. Furthermore, the key elements of psychological interventions found to be successful in managing diabetes are yet to be implemented in DFU risk management. Importantly, research evidence indicates that commonly advocated foot self-care recommendations may be insufficient in preventing DFU recurrence, whereas digital technology appears to effectively reduce recurrent DFU. More research is therefore needed to identify determinants of patient acceptance of digital technology.

A novel diabetic foot ulcer diagnostic model: identification and analysis of genes related to glutamine metabolism and immune infiltration

BACKGROUND

Diabetic foot ulcer (DFU) is one of the most common and severe complications of diabetes, with vascular changes, neuropathy, and infections being the primary pathological mechanisms. Glutamine (Gln) metabolism has been found to play a crucial role in diabetes complications. This study aims to identify and validate potential Gln metabolism biomarkers associated with DFU through bioinformatics and machine learning analysis.

METHODS

We downloaded two microarray datasets related to DFU patients from the Gene Expression Omnibus (GEO) database, namely GSE134431, GSE68183, and GSE80178. From the GSE134431 dataset, we obtained differentially expressed Gln-metabolism related genes (deGlnMRGs) between DFU and normal controls. We analyzed the correlation between deGlnMRGs and immune cell infiltration status. We also explored the relationship between GlnMRGs molecular clusters and immune cell infiltration status. Notably, WGCNA to identify differentially expressed genes (DEGs) within specific clusters. Additionally, we conducted GSVA to annotate enriched genes. Subsequently, we constructed and screened the best machine learning model. Finally, we validated the predictions' accuracy using a nomogram, calibration curves, decision curve analysis (DCA), and the GSE134431, GSE68183, and GSE80178 dataset.

RESULTS

In both the DFU and normal control groups, we confirmed the presence of deGlnMRGs and an activated immune response. From the GSE134431 dataset, we obtained 20 deGlnMRGs, including CTPS1, NAGS, SLC7A11, GGT1, GCLM, RIMKLA, ARG2, ASL, ASNS, ASNSD1, PPAT, GLS2, GLUD1, MECP2, ASS1, PRODH, CTPS2, ALDH5A1, DGLUCY, and SLC25A12. Furthermore, two clusters were identified in DFU. Immune infiltration analysis indicated the presence of immune heterogeneity in these two clusters. Additionally, we established a Support Vector Machine (SVM) model based on 5 genes (R3HCC1, ZNF562, MFN1, DRAM1, and PTGDS), which exhibited excellent performance on the external validation datasetGSE134431, GSE68183, and GSE80178 (AUC = 0.929).

CONCLUSION

This study has identified five Gln metabolism genes associated with DFU, revealing potential novel biomarkers and therapeutic targets for DFU. Additionally, the infiltration of immune-inflammatory cells plays a crucial role in the progression of DFU.

Psychosocial Care for People With Diabetic Neuropathy: Time for Action

Psychological factors and psychosocial care for individuals with diabetic neuropathy (DN), a common and burdensome complication of diabetes, are important but overlooked areas. In this article we focus on common clinical manifestations of DN, unremitting neuropathic pain, postural instability, and foot complications, and their psychosocial impact, including depression, anxiety, poor sleep quality, and specific problems such as fear of falling and fear of amputation. We also summarize the evidence regarding the negative impact of psychological factors such as depression on DN, self-care tasks, and future health outcomes. The clinical problem of underdetection and undertreatment of psychological problems is described, together with the value of using brief assessments of these in clinical care. We conclude by discussing trial evidence regarding the effectiveness of current pharmacological and nonpharmacological approaches and also future directions for developing and testing new psychological treatments for DN and its clinical manifestations.

Synergizing Intelligence and Building a Smarter Future: Artificial Intelligence Meets Bioengineering

Smart Engineering (SE) describes the methods, processes, and IT tools for the interdisciplinary, system-oriented development of innovative, intelligent, networked products, production plants, and infrastructures [...].

Distal Metatarsal Osteotomies for Chronic Plantar Diabetic Foot Ulcers

In more than 30 years of scientific literature (1986-2021), the few published studies on the management of CPDFUs by DMOs showed satisfactory clinical and radiographic outcomes. Although these reports were all case series, their data suggest that DMOs, performed at a different level of the distal metatarsal bones, are an effective surgical treatment option for achieving rapid healing of CPDFUs and preventing their recurrence after balancing the pressures in diabetic forefeet. Hence, DMOs can be a valid alternative treatment method also for CPDFUs with chronic infection, ulcers penetrating deep structures, and even ulcers with osteomyelitis at the metatarsophalangeal level.