Mobile app for Diabetic Foot Self-Care

NewsBot · Jun 12, 2020

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Usability of a Mobile Application on Diabetic Foot Self-Care
Antonio Dean Barbosa Marques
Rev Bras Enferm. 2020 Jun 8;73(4)

Objectives: to assess the usability of an app prototype for diabetic foot self-care by an end user.

Methods: a descriptive study that uses heuristic assessment of a hybrid app usability. Fifteen users of an outpatient diabetes care service in a capital of Northeastern Brazil participated in the study during April 2018. The usability measurement tool called Smartphone Usability questionnaiRE was applied.

Results: the lowest score was 77 and the highest was 112, with an average usability of 96.1 points. Usability was framed in the last two levels, 70 and 8o. Users now strongly agree (level 70) and fully (level 80) with the assessed items, which represents good usability of the apps prototype.

Conclusions: the final product developed focuses on user needs and requirements, which can ensure usability based on effectiveness, efficiency and satisfaction triad.
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NewsBot · Jun 12, 2020

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NewsBot · Oct 24, 2020

Utilization of smartphone and tablet camera photographs to predict healing of diabetes-related foot ulcers
Renaid B Kim et al
Comput Biol Med. 2020 Oct 8;126:104042

The objective of this study was to build a machine learning model that can predict healing of diabetes-related foot ulcers, using both clinical attributes extracted from electronic health records (EHR) and image features extracted from photographs. The clinical information and photographs were collected at an academic podiatry wound clinic over a three-year period. Both hand-crafted color and texture features and deep learning-based features from the global average pooling layer of ResNet-50 were extracted from the wound photographs. Random Forest (RF) and Support Vector Machine (SVM) models were then trained for prediction. For prediction of eventual wound healing, the models built with hand-crafted imaging features alone outperformed models built with clinical or deep-learning features alone. Models trained with all features performed comparatively against models trained with hand-crafted imaging features. Utilization of smartphone and tablet photographs taken outside of research settings hold promise for predicting prognosis of diabetes-related foot ulcers.
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NewsBot · Jun 13, 2022

Can weekly ‘foot alerts’ using a bespoke mobile app improve patient diabetic foot care knowledge and practices in Kuwait
K. Scarsbrook Khan
VOLUME 186, SUPPLEMENT 1, 109413, APRIL 01, 2022

Background: Diabetic foot ulcers (DFU) are the leading cause of non-traumatic lower limb amputation, occurring every 20-secs. An important step in disrupting the pathway to amputation is improving patient awareness and foot care practices. Improvement in short-term knowledge and behaviour following education programs has been reported, but without sustained improvement. Two recent Cochrane reviews reported that not enough high-quality evidence existed to prove the effectiveness of patient education programs on the prevention of DFU, as delivery methods are not evidence-based, nor are the right patients targeted. We propose that patients who receive weekly foot alerts alongside their regular Podiatry appointments will have better foot care knowledge and behaviours at 12-months compared to a control group.
Aim: This study aims to determine if targeted weekly diabetic foot alerts improve diabetic foot care behaviour and knowledge in patients with high and moderate diabetic foot risk classification, compared to participants who only receive regular podiatry interventions.
Method: This randomized, investigator-blinded, two-armed, study aims to pilot an innovative approach to education delivery. Participants will be included if they have been classified as high or moderate risk of developing DFU using the NICE classification system. Ninety-eight Participants will be randomised to (1) control group, who will receive usual diabetic foot care education, including daily foot inspections, foot hygiene, and footwear advice, supplemented by an information leaflet or (2) intervention group, in addition to the diabetic foot care education and information leaflet given to the control group, participants will receive a 10-minute audio-visual pre-recorded presentation based on the foot care education and an application will be downloaded onto their smart phone. This application will deliver weekly foot alerts based on the presentation, repeating at 12-weekly intervals. Podiatry appointments will be scheduled depending on risk classification. Participants will complete an adapted Summary of Diabetes Self-Care Activities behaviour questionnaire (SDSCA) and a Foot Care Knowledge questionnaire at first Podiatry appointment and 12-months.
Results: The primary outcome measure will compare means of each questionnaire between the two groups. It is anticipated that participants in the intervention group will have improved foot care knowledge and practices. Secondary outcomes will include assessing the association between participants knowledge and behaviour and the number of foot alert engagements, and the number of podiatry appointments. Lastly, the number of new DFUs and change in HbA1c will be compared between the two groups.
Discussion: This novel approach to diabetic foot care education could have a significant impact on patients' foot health and quality of life. Moreover, the financial burden to healthcare facilities and governments may be lessened by improving foot care behaviour and reducing DFU frequency.
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NewsBot · Apr 16, 2024

Application of a Diabetic Foot Smart APP in the measurement of diabetic foot ulcers
Nan Zhao et al
Int J Orthop Trauma Nurs. 2024 Mar 22:54:101095

Aims: In the early stage, we developed an intelligent measurement APP for diabetic foot ulcers, named Diabetic Foot Smart APP. This study aimed to validate the APP in the measurement of ulcer area for diabetic foot ulcer (DFU).

Methods: We selected 150 DFU images to measure the ulcer areas using three assessment tools: the Smart APP software package, the ruler method, and the gold standard Image J software, and compared the measurement results and measurement time of the three tools. The intra-rater and inter-rater reliability were described by Pearson correlation coefficient, intra-group correlation coefficient, and coefficient of variation.

Results: The Image J software showed a median ulcer area of 4.02 cm2, with a mean measurement time of 66.37 ± 7.95 s. The ruler method showed a median ulcer area of 5.14 cm2, with a mean measurement time of 171.47 ± 46.43 s. The APP software showed a median ulcer area of 3.70 cm2, with a mean measurement time of 38.25 ± 6.81 s. There were significant differences between the ruler method and the golden standard Image J software (Z = -4.123, p < 0.05), but no significant difference between the APP software and the Image J software (Z = 1.103, p > 0.05). The APP software also showed good inter-rater reliability and intra-rater reliability, with both reaching 0.99.

Conclusion: The Diabetic Foot Smart APP is a fast and reliable measurement tool with high measurement accuracy that can be easily used in clinical practice for the measurement of ulcer areas of DFU.
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