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EMG analysis across different tasks improves prevention screenings in diabetes: a cluster analysis approach.

ABSTRACT: The aim of this work was twofold: on one side to determine the most suitable parameters of surface electromyography (sEMG) to classify diabetic subjects with and without neuropathy and discriminate them from healthy controls and second to assess the role of the task acquired in the classification process. For this purpose 30 subjects were examined (10 controls, 10 diabetics with and 10 without neuropathy) whilst walking and stair ascending and descending. The electrical activity of six muscles was recorded bilaterally through a 16-channel sEMG system synchronised with a stereophotogrammetric system: Rectus Femoris, Gluteus Medius, Tibialis Anterior, Peroneus Longus, Gastrocnemius Lateralis and Extensor Digitorum. Spatiotemporal parameters of gait and stair climbing and the following sEMG parameters were extracted: signal envelope, activity duration, timing of activation and deactivation. A hierarchical clustering algorithm was applied to the whole set of parameters with different distances and linkage methods. Results showed that only by applying the Ward agglomerative hierarchical clustering (Hamming distance) to the all set of parameters extracted from both tasks, 5 well-separated clusters were obtained: cluster 3 included only DS subjects, cluster 2 and 4 only controls and cluster 1 and 5 only DNS subjects. This method could be used for planning rehabilitation treatments.

SUBMITTER: Piatkowska W

PROVIDER: S-EPMC9079040 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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EMG analysis across different tasks improves prevention screenings in diabetes: a cluster analysis approach.

Piatkowska Weronika W Spolaor Fabiola F Guiotto Annamaria A Guarneri Gabriella G Avogaro Angelo A Sawacha Zimi Z

Medical & biological engineering & computing 20220415 6

The aim of this work was twofold: on one side to determine the most suitable parameters of surface electromyography (sEMG) to classify diabetic subjects with and without neuropathy and discriminate them from healthy controls and second to assess the role of the task acquired in the classification process. For this purpose 30 subjects were examined (10 controls, 10 diabetics with and 10 without neuropathy) whilst walking and stair ascending and descending. The electrical activity of six muscles w ...[more]

PMID: 35428958

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Project description:IntroductionThe Diabetes Prevention Program, an intensive lifestyle change program, effectively reduces the risk of progression from prediabetes to type 2 diabetes but is underutilized. An implementation study using formative research was undertaken to increase Diabetes Prevention Program referrals at a primary care clinic.Study designA pragmatic, cluster randomized, mixed-methods study.Setting/particpantsClusters were teams of primary care clinicians from 2 primary care clinics. The 3 intervention clusters had 8-11 clinicians, and the 3 control clusters had 7-20 clinicians.InterventionImplementation activities occurred from December 2017 to February 2019. The activities included targeted clinician education, a prediabetes clinician champion, and a custom electronic health record report identifying patients with prediabetes.Main outcome measuresThe primary outcome was referral of patients with prediabetes to the institutional Diabetes Prevention Program. Study data, including patient demographic and clinical variables, came from electronic health record. Interviews with clinicians evaluated the implementation strategies. Generalized estimating equation analyses that accounted for multiple levels of correlation and interview content analysis occurred in 2019.ResultsStudy clinicians cared for 2,992 patients with a prediabetes diagnosis or HbA1c indicative of prediabetes (5.7%-6.4%). Clinicians in the intervention clusters referred 6.9% (87 of 1,262) of patients with prediabetes to the Diabetes Prevention Program and those in the control clusters referred 1.5% (26 of 1,730). When adjusted for patient age, sex, race, HbA1c value, HbA1c test location, and insurance type, intervention clinicians had 3.85 (95% CI=0.40, 36.78) greater odds of referring a patient with prediabetes to the Diabetes Prevention Program. The 11 interviewed intervention clinicians had mixed opinions about the utility of the interventions, reporting the prediabetes clinic champion (n=7, 64%) and educational presentations (n=6, 55%) as most helpful.ConclusionsIntervention clinicians were more likely to make Diabetes Prevention Program referrals; however, the study lacked power to achieve statistical significance. Clinician interviews suggested that intervention components that triggered Diabetes Prevention Program referrals varied among clinicians.

Dataset Information

EMG analysis across different tasks improves prevention screenings in diabetes: a cluster analysis approach.

Publications

EMG analysis across different tasks improves prevention screenings in diabetes: a cluster analysis approach.

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