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Higgins S, Dutta S, Kakar RS. Machine learning for lumbar and pelvis kinematics clustering. Comput Methods Biomech Biomed Engin 2024; 27:1332-1345. [PMID: 37548432 DOI: 10.1080/10255842.2023.2241593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 07/07/2023] [Accepted: 07/20/2023] [Indexed: 08/08/2023]
Abstract
Clustering algorithms such as k-means and agglomerative hierarchical clustering (HCA) may provide a unique opportunity to analyze time-series kinematic data. Here we present an approach for determining number of clusters and which clustering algorithm to use on time-series lumbar and pelvis kinematic data. Cluster evaluation measures such as silhouette coefficient, elbow method, Dunn Index, and gap statistic were used to evaluate the quality of decision making. The result show that multiple clustering evaluation methods should be used to determine the ideal number of clusters and algorithm suitable for clustering time-series data for each dataset being analyzed.
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Affiliation(s)
- Seth Higgins
- Human Movement Science, Oakland University, Rochester Hills, MI, USA
| | - Sandipan Dutta
- Mathematics and Statistics, Old Dominion University, Norfolk, VA, USA
| | - Rumit Singh Kakar
- Human Movement Science, Oakland University, Rochester Hills, MI, USA
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2
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Mahmoud A, Romanato M, Squartini G, Ruggiero A, Spigarelli F, Morgantini A, De Tanti A, Spagnuolo C, Sawacha Z. Clinical gait analysis reveals altered walking patterns in critical Covid 19 survivors. Clin Biomech (Bristol, Avon) 2024; 118:106318. [PMID: 39116645 DOI: 10.1016/j.clinbiomech.2024.106318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 07/09/2024] [Accepted: 07/30/2024] [Indexed: 08/10/2024]
Abstract
BACKGROUND Covid-19 has dramatically increased the number of admissions in intensive care units due to respiratory complications. In some cases, the arousal of neurological impairments, such as peripheral neuropathies, have been revealed. The purpose of this research was to characterize the gait pattern and muscle activity changes in Covid-19 survivors compared to physiological gait. METHODS Twelve post-Covid-19 participants admitted to intensive care units and twelve non-disabled controls were considered. Kinematics, kinetics and surface electromyographic data were collected for each participant during walking. Post Covid-19 participants were further divided into two sub-groups, according to the number of days spent in the intensive care units. Lower limb joint angles, moments and powers were extracted as well as the muscle activity of four muscles bilaterally, the spatial, temporal and spatiotemporal parameters of gait and the ground reaction forces. The extracted variables were compared through OneWay-ANOVA or Kruskal-Wallis tests where appropriate (p < 0.05). FINDINGS Overall, the considered parameters revealed statistically significant reduction in gait speed, cadence, range of motion in the sagittal plane, anteroposterior and vertical ground reaction forces between pathological and control participants. Larger alterations of the gait patterns were highlighted in the post-Covid-19 group hospitalized in intensive care units longer than 35 days, where a reduced muscle activity was observed on all the analyzed muscles. INTERPRETATION Results suggested that the severity of gait impairments in post-Covid-19 participants might be correlated with intensive care units-bedding period. Gait biomechanics assessment could be adopted in the clinical decision-making process to improve treatment protocols in post-Covid-19 survivors.
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Affiliation(s)
| | - Marco Romanato
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Giulia Squartini
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Antonio Ruggiero
- Santo Stefano Rehabilitation Institute, KOS Care, Porto Potenza Picena, Macerata, Italy
| | - Francesco Spigarelli
- Santo Stefano Rehabilitation Institute, KOS Care, Porto Potenza Picena, Macerata, Italy
| | - Antonello Morgantini
- Santo Stefano Rehabilitation Institute, KOS Care, Porto Potenza Picena, Macerata, Italy
| | | | - Chiara Spagnuolo
- Santo Stefano Rehabilitation Institute, KOS Care, Porto Potenza Picena, Macerata, Italy
| | - Zimi Sawacha
- Department of Information Engineering, University of Padova, Padova, Italy.
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Scalona E, De Marco D, Ferrari L, Creatini I, Taglione E, Andreoni G, Fabbri-Destro M, Avanzini P, Lopomo NF. Identification of movement phenotypes from occupational gesture kinematics: Advancing individual ergonomic exposure classification and personalized training. APPLIED ERGONOMICS 2024; 115:104182. [PMID: 38000137 DOI: 10.1016/j.apergo.2023.104182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 11/10/2023] [Accepted: 11/15/2023] [Indexed: 11/26/2023]
Abstract
The identification of personalized preventive strategies plays a major role in contrasting the occurrence of work-related musculoskeletal disorders. This requires the identification of distinct movement patterns within large samples and the attribution of a proper risk level to each identified movement phenotype. We assessed the feasibility of this approach by exploiting wearable inertial measurement units to estimate the whole-body kinematics of 43 healthy participants performing 18 reach-to-manipulate movements, which differed based on the object's position in the space and the type of manipulation required. Through unsupervised clustering, we identified multiple movement phenotypes graded by ergonomic performance. Furthermore, we determined which joints mostly contributed to instantiating the ergonomic differences across clusters, emphasizing the importance of monitoring this aspect during occupational gestures. Overall, our analysis suggests that movement phenotypes can be identified within occupational motor repertoires. Assigning individual performance to specific phenotypes has the potential to inform the development of more effective and tailored interventions.
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Affiliation(s)
- Emilia Scalona
- Dipartimento di Scienze Medico Chirurgiche, Scienza Radiologiche e Sanità Pubblica (DSMC), Università Degli Studi di Brescia, Viale Europa 11, 25123, Brescia, Italy.
| | - Doriana De Marco
- Dipartimento di Medicina e Chirurgia, Università Degli Studi di Parma, Parma, Italy
| | - Laura Ferrari
- Consiglio Nazionale Delle Ricerche, Istituto di Neuroscienze, Parma, Italy; School of Advanced Studies, Università di Camerino, Camerino, Italy
| | | | - Elisa Taglione
- Centro di Riabilitazione Motoria, INAIL, Volterra, Italy
| | | | | | - Pietro Avanzini
- Consiglio Nazionale Delle Ricerche, Istituto di Neuroscienze, Parma, Italy
| | - Nicola Francesco Lopomo
- Consiglio Nazionale Delle Ricerche, Istituto di Neuroscienze, Parma, Italy; Dipartimento di Ingegneria Dell'Informazione, Università Degli Studi di Brescia, Brescia, Italy
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Pauk J, Daunoraviciene K, Ziziene J, Minta-Bielecka K, Dzieciol-Anikiej Z. Classification of muscle activity patterns in healthy children using biclustering algorithm. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2023.104731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2023]
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EMG analysis across different tasks improves prevention screenings in diabetes: a cluster analysis approach. Med Biol Eng Comput 2022; 60:1659-1673. [PMID: 35428958 PMCID: PMC9079040 DOI: 10.1007/s11517-022-02559-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 03/27/2022] [Indexed: 11/01/2022]
Abstract
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.
Graphical abstract
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Haque F, Reaz MBI, Chowdhury MEH, Ezeddin M, Kiranyaz S, Alhatou M, Ali SHM, Bakar AAA, Srivastava G. Machine Learning-Based Diabetic Neuropathy and Previous Foot Ulceration Patients Detection Using Electromyography and Ground Reaction Forces during Gait. SENSORS (BASEL, SWITZERLAND) 2022; 22:3507. [PMID: 35591196 PMCID: PMC9100406 DOI: 10.3390/s22093507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 03/31/2022] [Accepted: 04/02/2022] [Indexed: 11/16/2022]
Abstract
Diabetic neuropathy (DN) is one of the prevalent forms of neuropathy that involves alterations in biomechanical changes in the human gait. Diabetic foot ulceration (DFU) is one of the pervasive types of complications that arise due to DN. In the literature, for the last 50 years, researchers have been trying to observe the biomechanical changes due to DN and DFU by studying muscle electromyography (EMG) and ground reaction forces (GRF). However, the literature is contradictory. In such a scenario, we propose using Machine learning techniques to identify DN and DFU patients by using EMG and GRF data. We collected a dataset from the literature which involves three patient groups: Control (n = 6), DN (n = 6), and previous history of DFU (n = 9) and collected three lower limb muscles EMG (tibialis anterior (TA), vastus lateralis (VL), gastrocnemius lateralis (GL)), and three GRF components (GRFx, GRFy, and GRFz). Raw EMG and GRF signals were preprocessed, and different feature extraction techniques were applied to extract the best features from the signals. The extracted feature list was ranked using four different feature ranking techniques, and highly correlated features were removed. In this study, we considered different combinations of muscles and GRF components to find the best performing feature list for the identification of DN and DFU. We trained eight different conventional ML models: Discriminant analysis classifier (DAC), Ensemble classification model (ECM), Kernel classification model (KCM), k-nearest neighbor model (KNN), Linear classification model (LCM), Naive Bayes classifier (NBC), Support vector machine classifier (SVM), and Binary decision classification tree (BDC), to find the best-performing algorithm and optimized that model. We trained the optimized the ML algorithm for different combinations of muscles and GRF component features, and the performance matrix was evaluated. Our study found the KNN algorithm performed well in identifying DN and DFU, and we optimized it before training. We found the best accuracy of 96.18% for EMG analysis using the top 22 features from the chi-square feature ranking technique for features from GL and VL muscles combined. In the GRF analysis, the model showed 98.68% accuracy using the top 7 features from the Feature selection using neighborhood component analysis for the feature combinations from the GRFx-GRFz signal. In conclusion, our study has shown a potential solution for ML application in DN and DFU patient identification using EMG and GRF parameters. With careful signal preprocessing with strategic feature extraction from the biomechanical parameters, optimization of the ML model can provide a potential solution in the diagnosis and stratification of DN and DFU patients from the EMG and GRF signals.
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Affiliation(s)
- Fahmida Haque
- Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia; (F.H.); (S.H.M.A.); (A.A.A.B.)
| | - Mamun Bin Ibne Reaz
- Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia; (F.H.); (S.H.M.A.); (A.A.A.B.)
| | | | - Maymouna Ezeddin
- Department of Electrical Engineering, Qatar University, Doha 2713, Qatar; (M.E.); (S.K.)
| | - Serkan Kiranyaz
- Department of Electrical Engineering, Qatar University, Doha 2713, Qatar; (M.E.); (S.K.)
| | - Mohammed Alhatou
- Neuromuscular Division, Hamad General Hospital, Doha 3050, Qatar;
- Department of Neurology, Al khor Hospital, Doha 3050, Qatar
| | - Sawal Hamid Md Ali
- Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia; (F.H.); (S.H.M.A.); (A.A.A.B.)
| | - Ahmad Ashrif A Bakar
- Department of Electrical, Electronic and System Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia; (F.H.); (S.H.M.A.); (A.A.A.B.)
| | - Geetika Srivastava
- Department of Physics and Electronics, Dr. Ram Manohar Lohia Avadh University, Faizabad, Uttar Pradesh 224001, India;
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Wang Z, Peng S, Zhang H, Sun H, Hu J. Gait Parameters and Peripheral Neuropathy in Patients With Diabetes: A Meta-Analysis. Front Endocrinol (Lausanne) 2022; 13:891356. [PMID: 35721708 PMCID: PMC9199374 DOI: 10.3389/fendo.2022.891356] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 04/27/2022] [Indexed: 01/13/2023] Open
Abstract
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.
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Affiliation(s)
- Zhenchao Wang
- Department of Endocrinology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Si Peng
- Department of Endocrinology, The Second Affiliated Hospital of Soochow University, Suzhou, China
- Department of Endocrinology, Shanghai Pudong New Area People's Hospital, Shanghai, China
| | - Honghong Zhang
- Department of Endocrinology, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Hong Sun
- Department of Traditional Chinese Medicine, The Second Affiliated Hospital of Soochow University, Suzhou, China
- *Correspondence: Hong Sun, ; Ji Hu,
| | - Ji Hu
- Department of Endocrinology, The Second Affiliated Hospital of Soochow University, Suzhou, China
- *Correspondence: Hong Sun, ; Ji Hu,
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Iatcu CO, Steen A, Covasa M. Gut Microbiota and Complications of Type-2 Diabetes. Nutrients 2021; 14:nu14010166. [PMID: 35011044 PMCID: PMC8747253 DOI: 10.3390/nu14010166] [Citation(s) in RCA: 118] [Impact Index Per Article: 39.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 12/24/2021] [Accepted: 12/29/2021] [Indexed: 12/12/2022] Open
Abstract
The gut microbiota has been linked to the emergence of obesity, metabolic syndrome and the onset of type 2 diabetes through decreased glucose tolerance and insulin resistance. Uncontrolled diabetes can lead to serious health consequences such as impaired kidney function, blindness, stroke, myocardial infarction and lower limb amputation. Despite a variety of treatments currently available, cases of diabetes and resulting complications are on the rise. One promising new approach to diabetes focuses on modulating the gut microbiota with probiotics, prebiotics, synbiotics and fecal microbial transplantation. Differences in gut microbiota composition have been observed in preclinical animal models as well as patients with type 2 diabetes and complications such as diabetic nephropathy, diabetic retinopathy, diabetic neuropathy, cerebrovascular disease, coronary heart disease and peripheral artery disease compared to healthy controls. Severity of gut microbiota dysbiosis was associated with disease severity and restoration with probiotic administration in animal models and human patients has been associated with improvement of symptoms and disease progression. Characterizing the gut microbiota dysbiosis in different diseases and determining a causal relationship between the gut microbiota and disease can be beneficial in formulating therapeutic interventions for type 2 diabetes and associated complications. In this review, we present the most important findings regarding the role of the gut microbiota in type 2 diabetes and chronic complications as well as their underlying mechanisms.
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Affiliation(s)
- Camelia Oana Iatcu
- College of Medicine and Biological Sciences, Stefan cel Mare University of Suceava, 720229 Suceava, Romania;
- College of Medicine, “Grigore T. Popa” University of Medicine and Pharmacy, 700115 Iasi, Romania
| | - Aimee Steen
- Department of Basic Medical Sciences, College of Osteopathic Medicine, Western University of Health Sciences, Pomona, CA 91766, USA;
| | - Mihai Covasa
- College of Medicine and Biological Sciences, Stefan cel Mare University of Suceava, 720229 Suceava, Romania;
- Department of Basic Medical Sciences, College of Osteopathic Medicine, Western University of Health Sciences, Pomona, CA 91766, USA;
- Correspondence:
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Bartolo E, Giacomozzi C, Coppini DV, Gatt A. The effect of induced joint restriction on plantar pressure during gait - a pilot study. Gait Posture 2021; 90:23-28. [PMID: 34365284 DOI: 10.1016/j.gaitpost.2021.07.019] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 06/14/2021] [Accepted: 07/24/2021] [Indexed: 02/02/2023]
Abstract
BACKGROUND The aim of this study was to analyse the effect of induced lower limb joint restriction on plantar pressures during gait. Focusing on restricting a single joint, without the effect of other co-morbidities, would provide better understanding as to the resultant plantar loadings during gait, which would be especially beneficial in patients requiring offloading procedures. RESEARCH QUESTION Does induced lower limb joint restriction affect plantar pressure distribution during gait? METHODS A prospective, quasi-experimental study was conducted, recruiting ten healthy, adult participants who were instructed to walk barefoot over a Tekscan HR Mat™. This procedure was repeated after separately inducing restriction of the hip, knee and ankle joints. Mean peak plantar pressure (MPP) and pressure-time integral (PTI) data were analysed to compare between unrestricted and restricted data. RESULTS Significant plantar pressure changes were observed in the heel and first metatarsal regions. Rearfoot PTIs were increased with restriction of the contralateral hip (left p <0.001) (right p =0.02) and knee joints (left p =0.01) (right p =0.04). Both MPPs (left p =0.01; right p =0.01) and PTIs (left p =0.004; right p =0.03) were increased in the first metatarsal when restricting the hip joint of the same limb. MPP was decreased in the left first metatarsal with induced knee (left p =0.01; right p =0.04) and ankle (left and right p <0.001) joint restriction. Finally, MPP was decreased in the right first metatarsal with knee (left and right p =0.01) and ankle (left p =0.04; right p =0.01) joint restriction. SIGNIFICANCE Limited joint mobility may have a direct effect on plantar pressure, particularly with restriction in the hip and knee joints, hence careful attention should be given especially in patients with conditions involving plantar loadings. Results in this study also show that PTI changes during gait should be equally evaluated clinically along with peak plantar pressure analysis.
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Affiliation(s)
- Erica Bartolo
- Faculty of Health Sciences, University of Malta, Msida, Malta.
| | - Claudia Giacomozzi
- Department of Cardiovascular Diseases, Dysmetabolic Diseases & Ageing, Italian National Institute of Health, Rome, Italy.
| | | | - Alfred Gatt
- Faculty of Health Sciences, University of Malta, Msida, Malta.
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Classification of Diabetic Walking for Senior Citizens and Personal Home Training System Using Single RGB Camera through Machine Learning. APPLIED SCIENCES-BASEL 2021. [DOI: 10.3390/app11199029] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Senior citizens have increased plasma glucose and a higher risk of diabetes-related complications than young people. However, it is difficult to diagnose and manage elderly diabetics because there is no clear symptom according to current diagnostic criteria. They also dislike the invasive blood sample test. This study aimed to classify a difference in gait and physical fitness characteristics between senior citizens with and without diabetes for a non-invasive method and propose a machine-learning-based personal home-training system for training abnormal gait motions by oneself. We used a dataset for classification with 200 over 65-year-old elders who walked a flat and straight 15 m route in 3 different walking speed conditions using an inertial measurement unit and physical fitness test. Then, questionnaires for participants were included to identify life patterns. Through results, it was found that there were abnormalities in gait and physical fitness characteristics related to balance ability and walking speed. Using a single RGB camera, the developed training system for improving abnormalities enabled us to correct the exercise posture and speed in real-time. It was discussed that there are risks and errors in the training system based on human pose estimation for future works.
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Romanato M, Volpe D, Guiotto A, Spolaor F, Sartori M, Sawacha Z. Electromyography-informed modeling for estimating muscle activation and force alterations in Parkinson's disease. Comput Methods Biomech Biomed Engin 2021; 25:14-26. [PMID: 33998843 DOI: 10.1080/10255842.2021.1925887] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Electromyography (EMG)-driven neuromusculoskeletal modeling (NMSM) enables simulating the mechanical function of multiple muscle-tendon units as controlled by nervous system in the generation of complex movements. In the context of clinical assessment this may enable understanding biomechanical factor contributing to gait disorders such as one induced by Parkinson's disease (PD). In spite of the challenges in the development of patient-specific models, this preliminary study aimed at establishing a feasible and noninvasive experimental and modeling pipeline to be adopted in clinics to detect PD-induced gait alterations. Four different NMSM have been implemented for three healthy controls using CEINMS, an OpenSim-compatible toolbox. Models differed in the EMG-normalization methods used for calibration purposes (i.e. walking trial normalization and maximum voluntary contraction normalization) and in the set of experimental EMGs used for the musculotendon-unit mapping (i.e. 4 channels vs. 15 channels). Model accuracy assessment showed no statistically significant differences between the more complete model (non-clinically viable) and the proposed reduced one (clinically viable). The clinically viable reduced model was systematically applied on a dataset including ten PD's and thirteen healthy controls. Results showed significant differences in the neuromuscular control strategy of the PD group in term of muscle forces and joint torques. Indeed, PD patients displayed a significantly lower magnitude on force production and revealed a higher amount of force variability with the respect of the healthy controls. The estimated variables could become a measurable biomechanical outcome to assess and track both disease progression and its impact on gait in PD subjects.
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Affiliation(s)
- Marco Romanato
- Department of Information Engineering, University of Padua, Padova, Italy
| | - Daniele Volpe
- Fresco Parkinson Center, Villa Margherita, Vicenza, Italy
| | - Annamaria Guiotto
- Department of Information Engineering, University of Padua, Padova, Italy
| | - Fabiola Spolaor
- Department of Information Engineering, University of Padua, Padova, Italy
| | - Massimo Sartori
- Department of Biomechanical Engineering, University of Twente, AE Enschede, Netherlands
| | - Zimi Sawacha
- Department of Information Engineering, University of Padua, Padova, Italy.,Department of Medicine, University of Padua, Padova, Italy
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Tian T, Wang C, Xu Y, Bai Y, Wang J, Long Z, Wang X, Zhou L. A Wearable Gait Analysis System Used in Type 2 Diabetes Mellitus Patients: A Case-Control Study. Diabetes Metab Syndr Obes 2021; 14:1799-1808. [PMID: 33935508 PMCID: PMC8079258 DOI: 10.2147/dmso.s305102] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 04/01/2021] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Previous studies have shown that the gait of patients with type-2 diabetes mellitus is abnormal compared with the healthy group. Currently, a three-dimensional motion analyzer system is commonly used for gait analysis. However, it is challenging to collect data and use in clinical study due to extensive experimental conditions and high price. In this study, we used a wearable gait analysis system (Gaitboter) to investigate the spatial and temporal parameters, and kinematic data of gait in diabetic patients, especially those with peripheral neuropathy. The aim of the study is to evaluate the wearable gait analysis system in diabetic study. MATERIALS AND METHODS We conducted a case-control study to analyze the gait of type 2 diabetes mellitus. Gaitboter was used to detect and collect gait data in the ward of Beijing Chao-yang Hospital, Capital Medical University from June 2018 to October 2018. We collected the gait data of participants (N= 146; 73 patients with type 2 diabetes, 16 with peripheral neuropathy and 57 without peripheral neuropathy, and 73 matched controls). The gait data (stance phase, swing phase, double-foot stance phase, single-foot stance phase, walking cadence, stride length, walking speed, off-ground angle, landing angle, maximum swing angle, minimum swing angle, and foot progression angle) in diabetic patients were recorded and compared with controls. SPSS 22.0 statistical software was used to analyzed the gait parameter data. RESULTS We found that the landing angle and the maximum swing angle of diabetes patients with or without peripheral neuropathy were significantly less than those of the control group (P < 0.05). The walking speed of diabetes patients with peripheral neuropathy is significantly less than those of the control group (P < 0.05). CONCLUSION This study confirms that the wearable gait analysis system (Gaitboter) is an ideal system to identify abnormal gait in patients with type 2 diabetes and provides a new device and method for diabetes-related gait research.
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Affiliation(s)
- Tian Tian
- General Practice Department, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, People’s Republic of China
| | - Cheng Wang
- Institute of Digital Economy Industry, ICT, Hangzhou, People’s Republic of China
- Luoyang Institute of Information Technology Industries, Luoyang, People’s Republic of China
- Ningbo Institute of Information Technology Application, CAS, Ningbo, People’s Republic of China
| | - Yuan Xu
- Department of Endocrinology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, People’s Republic of China
- Correspondence: Yuan Xu Email
| | - Yuzhi Bai
- General Practice Department, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, People’s Republic of China
| | - Jing Wang
- General Practice Department, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, People’s Republic of China
| | - Zhou Long
- Institute of Digital Economy Industry, ICT, Hangzhou, People’s Republic of China
- Luoyang Institute of Information Technology Industries, Luoyang, People’s Republic of China
| | - Xiangdong Wang
- Institute of Computing Technology (ICT), Chinese Academy of Sciences (CAS), Beijing, People’s Republic of China
- Beijing Key Laboratory of Mobile Computing and Pervasive Device, Beijing, People’s Republic of China
| | - Lichun Zhou
- Department of Neurosurgery, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, People’s Republic of China
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Alenazi AM, Alshehri MM, Alothman S, Alqahtani BA, Rucker J, Sharma NK, Bindawas SM, Kluding PM. The Association of Diabetes With Knee Pain Locations, Pain While Walking, and Walking Speed: Data From the Osteoarthritis Initiative. Phys Ther 2020; 100:1977-1986. [PMID: 32750122 PMCID: PMC7596886 DOI: 10.1093/ptj/pzaa144] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/02/2020] [Indexed: 01/14/2023]
Abstract
OBJECTIVE Osteoarthritis (OA) and diabetes mellitus (DM) often coexist and can result in negative outcomes. DM can affect pain and walking speed in people with knee OA; however, the impact of DM on OA is understudied. The purpose of this study was to investigate the association between diabetes and knee pain locations, pain severity while walking, and walking speed in people with knee OA. METHODS A cross-sectional analysis was used. Data from 1790 individuals from the Osteoarthritis Initiative (mean [SD] age = 69 [8.7] years) with knee pain were included and grouped into knee OA and diabetes (n = 236) or knee OA only (n = 1554). Knee pain locations were categorized as no pain, localized pain, regional pain, or diffuse pain. Knee pain during a 20-m walk test was categorized as no pain, mild, moderate, or severe knee pain. Walking speed was measured using the 20-m walk test. Multinomial and linear regression analyses were performed. RESULTS Diabetes was associated with regional knee pain (odds ratio [OR] = 1.77; 95% CI = 1.01-3.11). Diabetes was associated only with moderate (OR = 1.78; 95% CI = 1.02-3.10) or severe (OR = 2.52; 95% CI = 1.01-6.28) pain while walking. Diabetes was associated with decreased walking speed (B = -0.064; 95% CI = -0.09 to -0.03). CONCLUSIONS Diabetes was associated with regional knee pain but not with localized or diffuse knee pain and was associated with moderate to severe knee pain while walking and slower walking speed in people with knee OA. IMPACT Clinicians can use a knee pain map for examining knee pain locations for people with diabetes and knee OA. Knee pain during walking and walking speed should be screened for people with knee OA and diabetes because of the influence of diabetes on these parameters in this population. LAY SUMMARY Diabetes might be associated with specific knee pain locations, pain during activities such as walking, and reduced walking speed in people with knee OA.
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Affiliation(s)
| | | | - Shaima Alothman
- Lifestyle and Health Research Center, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia
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Sawacha Z, Sartor CD, Yi LC, Guiotto A, Spolaor F, Sacco ICN. Clustering classification of diabetic walking abnormalities: a new approach taking into account intralimb coordination patterns. Gait Posture 2020; 79:33-40. [PMID: 32334348 DOI: 10.1016/j.gaitpost.2020.03.016] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2019] [Revised: 03/13/2020] [Accepted: 03/27/2020] [Indexed: 02/02/2023]
Abstract
BACKGROUND It is well recognized that diabetes and peripheral neuropathy have a detrimental effect on gait. However, there are large variations in the results of studies addressing this aspect due to the heterogeneity of diabetic population in relation to presence and severity of diabetes complications. The aim of this study is to adopt an unsupervised classification technique to better elucidate the gait changes throughout the entire spectrum of diabetes and neuropathy. METHODS Sixty subjects were assessed and classified into four groups using a fuzzy logic model: 13 controls (55 ± 7years), 18 diabetics subjects without neuropathy (59 ± 6 years, 11 ± 7 diabetes years), 7 with mild neuropathy (56 ± 4years, 19 ± 7 diabetes years), and 22 with moderate to severe neuropathy (57 ± 5 years, 14 ± 8 diabetes years). Data were gathered by six infrared cameras at 100 Hz regarding lower limb joint kinematics (angles and angular velocities) and the relative phase for the hip-ankle, hip-knee, and knee-ankle were calculated. The K-means clustering algorithm was adopted to classify subjects considering the whole kinematics time series. A one-way ANOVA test was used to compare both clinical and kinematics parameters across clusters. RESULTS Only the classification based on the intralimb coordination variables succeeded in defining 5 well separated clusters with the following clinical characteristics: controls were grouped mainly in Cluster 2, diabetics in Cluster 4, and neuropathic subjects in Cluster 5 (which included various degrees of severity). Hip-ankle coordination in Clusters 4 and 5 were significantly different (p < 0.05) with respect to Cluster 2, mainly in the stance phase. During the swing phase, differences were observed in the ankle-knee coordination (p < 0.05) across clusters. CONCLUSION Classification based on intralimb coordination patterns succeeded in efficiently categorize gait alterations in diabetic subjects. It can be speculated that variables extracted from sagittal plane kinematics might be adopted as a support to clinical decision making in diabetes.
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Affiliation(s)
- Zimi Sawacha
- Department of Information Engineering, University of Padova, Padova, Italy; Department of Medicine, DIMED, University of Padova, Padova, Italy.
| | - Cristina D Sartor
- Ibirapuera University, São Paulo, Brazil; Physical Therapy, Speech and Occupational Therapy Department, School of Medicine, University of Sᾶo Paulo, São Paulo, Brazil.
| | - Liu Chiao Yi
- Federal University of Sao Paulo, Santos, São Paulo, Brazil.
| | - Annamaria Guiotto
- Department of Information Engineering, University of Padova, Padova, Italy.
| | - Fabiola Spolaor
- Department of Information Engineering, University of Padova, Padova, Italy.
| | - Isabel C N Sacco
- Physical Therapy, Speech and Occupational Therapy Department, School of Medicine, University of Sᾶo Paulo, São Paulo, Brazil.
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Remedios SM, Armstrong DP, Graham RB, Fischer SL. Exploring the Application of Pattern Recognition and Machine Learning for Identifying Movement Phenotypes During Deep Squat and Hurdle Step Movements. Front Bioeng Biotechnol 2020; 8:364. [PMID: 32426346 PMCID: PMC7212384 DOI: 10.3389/fbioe.2020.00364] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 03/31/2020] [Indexed: 12/29/2022] Open
Abstract
Background Movement screens are increasingly used in sport and rehabilitation to evaluate movement competency. However, common screens are often evaluated using subjective visual detection of a priori prescribed discrete movement features (e.g., spine angle at maximum squat depth) and may not account for whole-body movement coordination, or associations between different discrete features. Objective To apply pattern recognition and machine learning techniques to identify whole-body movement pattern phenotypes during the performance of exemplar functional movement screening tasks; the deep squat and hurdle step. Additionally, we also aimed to compare how discrete kinematic measures, commonly used to score movement competency, differed between emergent groups identified via pattern recognition and machine learning. Methods Principal component analysis (PCA) was applied to 3-dimensional (3D) trajectory data from participant's deep squat (DS) and hurdle step performance, identifying emerging features that describe orthogonal modes of inter-trial variance in the data. A gaussian mixture model (GMM) was fit and used to cluster the principal component scores as an unsupervised machine learning approach to identify emergent movement phenotypes. Between group features were analyzed using a one-way ANOVA to determine if the objective classifications were significantly different from one another. Results Three clusters (i.e., phenotypes) emerged for the DS and right hurdle step (RHS) and 4 phenotypes emerged for the left hurdle step (LHS). Selected discrete points commonly used to score DS and hurdle step movements were different between emergent groups. In regard to the select discrete kinematic measures, 4 out of 5, 7 out of 7 and 4 out of 7, demonstrated a main effect (p < 0.05) between phenotypes for the DS, RHS, and LHS respectively. Conclusion Findings support that whole-body movement analysis, pattern recognition and machine learning techniques can objectively identify movement behavior phenotypes without the need to a priori prescribe movement features. However, we also highlight important considerations that can influence outcomes when using machine learning for this purpose.
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Affiliation(s)
- Sarah M Remedios
- Occupational Biomechanics and Ergonomics Laboratory, Department of Kinesiology, University of Waterloo, Waterloo, ON, Canada
| | - Daniel P Armstrong
- Occupational Biomechanics and Ergonomics Laboratory, Department of Kinesiology, University of Waterloo, Waterloo, ON, Canada
| | - Ryan B Graham
- Spine Biomechanics Laboratory, School of Human Kinetics, University of Ottawa, Ottawa, ON, Canada
| | - Steven L Fischer
- Occupational Biomechanics and Ergonomics Laboratory, Department of Kinesiology, University of Waterloo, Waterloo, ON, Canada
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Silva EQ, Suda EY, Santos DP, Veríssimo JL, Ferreira JSSP, Cruvinel Júnior RH, Monteiro RL, Sartor CD, Sacco ICN. Effect of an educational booklet for prevention and treatment of foot musculoskeletal dysfunctions in people with diabetic neuropathy: the FOotCAre (FOCA) trial II, a study protocol of a randomized controlled trial. Trials 2020; 21:180. [PMID: 32054510 PMCID: PMC7020575 DOI: 10.1186/s13063-020-4115-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2020] [Accepted: 01/28/2020] [Indexed: 12/25/2022] Open
Abstract
Background This study is a part of a series of two clinical trials. We consider diabetic polyneuropathy (DPN), a common chronic and progressive complication of diabetes mellitus that has several impacts on individuals’ foot health and quality of life. Based on the current trends of self-monitoring and self-care, providing a tool with foot-related exercises and educational care may help patients to avoid or reduce the musculoskeletal complications resulting from DPN, improving autonomous performance in daily living tasks. The aim of this trial is to evaluate the effects of an educational booklet for foot care and foot muscle strengthening on DPN symptoms and severity, clinical outcomes, and gait biomechanics in patients with DPN. Methods/design The FOotCAre (FOCA) trial II study has been designed as a single-blind, two-parallel-arm randomized controlled trial. It will include 48 patients with DPN who will be randomly allocated to a control (recommended foot care by international consensus with no foot exercises) group or an intervention (foot-related exercises using an educational booklet three times/week at home for 8 weeks) group. Participants from both groups will be assessed at baseline, after 8 weeks, and at 16 weeks for follow-up. The primary outcomes are the DPN symptoms and severity, and the secondary outcomes are foot–ankle kinematics, gait kinetics, plantar pressure distribution during gait, tactile and vibratory sensitivities, foot strength, functional balance, and foot health and functionality. Discussion The booklet is a management tool that allows users to be autonomous in their treatment by choosing how and where to perform the exercises. This allows the patients to perform the exercises regularly as a continuous habit for foot care and health, which is an important element in the management of the diabetic foot. As the booklet focuses on specific foot–ankle exercises, we expect that it will improve the clinical aspects of DPN and produce beneficial biomechanical changes during gait, becoming a powerful self-management tool that can be easily implemented to improve the performance of daily living tasks. Trial registration ClinicalTrials.gov, NCT04008745. Registered on 2 July 2019.
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Affiliation(s)
- E Q Silva
- Department of Physical Therapy, Speech, and Occupational Therapy, School of Medicine, University of São Paulo, Rua Cipotânea, 51 - Cidade Universitária, São Paulo, São Paulo, 05360-160, Brazil
| | - E Y Suda
- Department of Physical Therapy, Speech, and Occupational Therapy, School of Medicine, University of São Paulo, Rua Cipotânea, 51 - Cidade Universitária, São Paulo, São Paulo, 05360-160, Brazil
| | - D P Santos
- Department of Physical Therapy, Speech, and Occupational Therapy, School of Medicine, University of São Paulo, Rua Cipotânea, 51 - Cidade Universitária, São Paulo, São Paulo, 05360-160, Brazil
| | - J L Veríssimo
- Department of Physical Therapy, Speech, and Occupational Therapy, School of Medicine, University of São Paulo, Rua Cipotânea, 51 - Cidade Universitária, São Paulo, São Paulo, 05360-160, Brazil
| | - J S S P Ferreira
- Department of Physical Therapy, Speech, and Occupational Therapy, School of Medicine, University of São Paulo, Rua Cipotânea, 51 - Cidade Universitária, São Paulo, São Paulo, 05360-160, Brazil
| | - R H Cruvinel Júnior
- Department of Physical Therapy, Speech, and Occupational Therapy, School of Medicine, University of São Paulo, Rua Cipotânea, 51 - Cidade Universitária, São Paulo, São Paulo, 05360-160, Brazil
| | - R L Monteiro
- Department of Physical Therapy, Speech, and Occupational Therapy, School of Medicine, University of São Paulo, Rua Cipotânea, 51 - Cidade Universitária, São Paulo, São Paulo, 05360-160, Brazil.,Department of Physical Therapy, Federal University of Amapá, Macapá, Amapá, Brazil
| | - C D Sartor
- Department of Physical Therapy, Ibirapuera University, São Paulo, São Paulo, Brazil
| | - I C N Sacco
- Department of Physical Therapy, Speech, and Occupational Therapy, School of Medicine, University of São Paulo, Rua Cipotânea, 51 - Cidade Universitária, São Paulo, São Paulo, 05360-160, Brazil.
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17
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Ferreira JSSP, Cruvinel Junior RH, Silva EQ, Veríssimo JL, Monteiro RL, Pereira DS, Suda EY, Sartor CD, Sacco ICN. Study protocol for a randomized controlled trial on the effect of the Diabetic Foot Guidance System (SOPeD) for the prevention and treatment of foot musculoskeletal dysfunctions in people with diabetic neuropathy: the FOotCAre (FOCA) trial I. Trials 2020; 21:73. [PMID: 31931855 PMCID: PMC6958734 DOI: 10.1186/s13063-019-4017-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2019] [Accepted: 12/19/2019] [Indexed: 01/29/2023] Open
Abstract
BACKGROUND This study is part of a series of two clinical trials. Taking into account the various musculoskeletal alterations of the foot and ankle in people with diabetic peripheral neuropathy (DPN) and the need for self-care to avoid more serious dysfunctions and complications, a self-manageable exercise protocol that focuses on strengthening the foot muscles is presented as a potentially effective preventive method for foot and gait complications. The aim of this trial is to investigate the effect of a customized rehabilitation technology, the Diabetic Foot Guidance System (SOPeD), on DPN status, functional outcomes and gait biomechanics in people with DPN. METHODS/DESIGN Footcare (FOCA) trial I is a randomized, controlled and parallel two-arm trial with blind assessment. A total of 62 patients with DPN will be allocated into either a control group (recommended foot care by international consensus with no foot exercises) or an intervention group (who will perform exercises through SOPeD at home three times a week for 12 weeks). The exercise program will be customized throughout its course by a perceived effort scale reported by the participant after completion of each exercise. The participants will be assessed at three different times (baseline, completion at 12 weeks, and follow-up at 24 weeks) for all outcomes. The primary outcomes will be DPN symptoms and severity classification. The secondary outcomes will be foot-ankle kinematics and kinetic and plantar pressure distribution during gait, tactile and vibration sensitivities, foot health and functionality, foot strength, and functional balance. DISCUSSION As there is no evidence about the efficacy of rehabilitation technology in reducing DPN symptoms and severity or improving biomechanical, clinical, and functional outcomes for people with DPN, this research can contribute substantially to clarifying the therapeutic merits of software interventions. We hope that the use of our application for people with DPN complications will reduce or attenuate the deficits caused by DPN. This rehabilitation technology is freely available, and we intend to introduce it into the public health system in Brazil after demonstrating its effectiveness. TRIAL REGISTRATION ClinicalTrials.gov, NCT04011267. Registered on 8 July 2019.
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Affiliation(s)
- J. S. S. P. Ferreira
- Department of Physical Therapy, Speech, and Occupational Therapy, School of Medicine, University of São Paulo, Rua Cipotânea, 51 - Cidade Universitária, São Paulo, São Paulo 05360-160 Brazil
| | - R. H. Cruvinel Junior
- Department of Physical Therapy, Speech, and Occupational Therapy, School of Medicine, University of São Paulo, Rua Cipotânea, 51 - Cidade Universitária, São Paulo, São Paulo 05360-160 Brazil
| | - E. Q. Silva
- Department of Physical Therapy, Speech, and Occupational Therapy, School of Medicine, University of São Paulo, Rua Cipotânea, 51 - Cidade Universitária, São Paulo, São Paulo 05360-160 Brazil
| | - J. L. Veríssimo
- Department of Physical Therapy, Speech, and Occupational Therapy, School of Medicine, University of São Paulo, Rua Cipotânea, 51 - Cidade Universitária, São Paulo, São Paulo 05360-160 Brazil
| | - R. L. Monteiro
- Department of Physical Therapy, Speech, and Occupational Therapy, School of Medicine, University of São Paulo, Rua Cipotânea, 51 - Cidade Universitária, São Paulo, São Paulo 05360-160 Brazil
- Department of Physical Therapy, Federal University of Amapá, Amapá, Brazil
| | - D. S. Pereira
- Department of Physical Therapy, Speech, and Occupational Therapy, School of Medicine, University of São Paulo, Rua Cipotânea, 51 - Cidade Universitária, São Paulo, São Paulo 05360-160 Brazil
| | - E. Y. Suda
- Department of Physical Therapy, Speech, and Occupational Therapy, School of Medicine, University of São Paulo, Rua Cipotânea, 51 - Cidade Universitária, São Paulo, São Paulo 05360-160 Brazil
| | - C. D. Sartor
- Department of Physical Therapy, Ibirapuera University, São Paulo, SP Brazil
| | - I. C. N. Sacco
- Department of Physical Therapy, Speech, and Occupational Therapy, School of Medicine, University of São Paulo, Rua Cipotânea, 51 - Cidade Universitária, São Paulo, São Paulo 05360-160 Brazil
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Mohseni S, Bayani M, Bahmani F, Tajabadi-Ebrahimi M, Bayani MA, Jafari P, Asemi Z. The beneficial effects of probiotic administration on wound healing and metabolic status in patients with diabetic foot ulcer: A randomized, double-blind, placebo-controlled trial. Diabetes Metab Res Rev 2018; 34. [PMID: 29193662 DOI: 10.1002/dmrr.2970] [Citation(s) in RCA: 74] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2017] [Revised: 11/05/2017] [Accepted: 11/20/2017] [Indexed: 01/05/2023]
Abstract
BACKGROUND This study was conducted to evaluate the effects of probiotic supplementation on wound healing and metabolic status in subjects with diabetic foot ulcer (DFU). METHODS This randomized, double-blind, placebo-controlled trial was conducted among 60 subjects (aged 40-85 years old) with grade 3 diabetic foot ulcer. Individuals were randomly divided into 2 groups (30 subjects each group) to receive either probiotic or placebo daily for 12 weeks. RESULTS After the 12-week intervention, compared with the placebo, probiotic supplementation led to significant reductions in ulcer length (-1.3 ± 0.9 vs. -0.8 ± 0.7 cm, P = .01), width (-1.1 ± 0.7 vs. -0.7 ± 0.7 cm, P = .02), and depth (-0.5 ± 0.3 vs. -0.3 ± 0.3 cm, P = .02). Furthermore, significant reductions in fasting plasma glucose (-29.6 ± 30.3 vs. -5.8 ± 39.8 mg/dL, P = .01), serum insulin concentrations (-4.3 ± 7.9 vs. +0.4 ± 8.5 μIU/mL, P = .03), and haemoglobin A1c (-0.6 ± 0.5 vs. -0.2 ± 0.4%, P = .003) and a significant rise in the quantitative insulin sensitivity check index (+0.01 ± 0.01 vs. -0.01 ± 0.02, P = .003) were seen following supplementation of probiotic compared with the placebo. Additionally, compared with the placebo, probiotic supplementation resulted in significant decreases in serum total cholesterol (-4.8 ± 16.1 vs. +7.0 ± 27.1 mg/dL, P = .04), high-sensitivity C-reactive protein (-9.0 ± 14.7 vs. -1.7 ± 8.6 mg/L, P = .02), plasma malondialdehyde (-0.8 ± 0.8 vs. -0.2 ± 0.8 μmol/L, P = .001), and significant increases in plasma nitric oxide (+6.2 ± 8.2 vs. +0.8 ± 8.0 μmol/L, P = .01) and total antioxidant capacity concentrations (+179.3 ± 97.2 vs. -85.1 ± 203.4 mmol/L, P < .001). CONCLUSIONS Overall, probiotic supplementation for 12 weeks among subjects with diabetic foot ulcer had beneficial effects on ulcer size, glycaemic control, total cholesterol, high-sensitivity C-reactive protein, plasma nitric oxide, total antioxidant capacity, and malondialdehyde levels.
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Affiliation(s)
- Sima Mohseni
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Masomeh Bayani
- Infectious Diseases and Tropical Medicine Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran
| | - Fereshteh Bahmani
- Research Center for Biochemistry and Nutrition in Metabolic Diseases, Kashan University of Medical Sciences, Kashan, Iran
| | | | - Mohammad Ali Bayani
- Department of Internal Medicine, School of Medicine, Babol University of Medical Sciences, Babol, Iran
| | - Parvaneh Jafari
- Department of Microbiology, Science Faculty, Islamic Azad University, Arak, Iran
| | - Zatollah Asemi
- Research Center for Biochemistry and Nutrition in Metabolic Diseases, Kashan University of Medical Sciences, Kashan, Iran
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Gomes AA, Ackermann M, Ferreira JP, Orselli MIV, Sacco ICN. Muscle force distribution of the lower limbs during walking in diabetic individuals with and without polyneuropathy. J Neuroeng Rehabil 2017; 14:111. [PMID: 29121964 PMCID: PMC5679149 DOI: 10.1186/s12984-017-0327-x] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2016] [Accepted: 10/31/2017] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Muscle force estimation could advance the comprehension of the neuromuscular strategies that diabetic patients adopt to preserve walking ability, which guarantees their independence as they deal with their neural and muscular impairments due to diabetes and neuropathy. In this study, the lower limb's muscle force distribution during gait was estimated and compared in diabetic patients with and without polyneuropathy. METHODS Thirty individuals were evaluated in a cross-sectional study, equally divided among controls (CG) and diabetic patients with (DNG) and without (DG) polyneuropathy. The acquired ground reaction forces and kinematic data were used as input variables for a scaled musculoskeletal model in the OpenSim software. The maximum isometric force of the ankle extensors and flexors was reduced in the model of DNG by 30% and 20%, respectively. The muscle force was calculated using static optimization, and peak forces were compared among groups (flexors and extensors of hip, knee, and ankle; ankle evertors; and hip abductors) using MANOVAs, followed by univariate ANOVAs and Newman-Keuls post-hoc tests (p < 0.05). RESULTS From the middle to late stance phase, DG showed a lower soleus muscle peak force compared to the CG (p=0.024) and the DNG showed lower forces in the gastrocnemius medialis compared to the DG (p=0.037). At the terminal swing phase, the semitendinosus and semimembranosus peak forces showed lower values in the DG compared to the CG and DNG. At the late stance, the DNG showed a higher peak force in the biceps short head, semimembranosus, and semitendinosus compared to the CG and DG. CONCLUSION Peak forces of ankle (flexors, extensors, and evertors), knee (flexors and extensors), and hip abductors distinguished DNG from DG, and both of those from CG. Both diabetic groups showed alterations in the force production of the ankle extensors with reductions in the forces of soleus (DG) and gastrocnemius medialis (DNG) seen in both diabetic groups, but only DNG showed an increase in the hamstrings (knee flexor) at push-off. A therapeutic approach focused on preserving the functionality of the knee muscles is a promising strategy, even if the ankle dorsiflexors and plantarflexors are included in the resistance training.
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Affiliation(s)
- Aline A. Gomes
- Physical Education and Physiotherapy Faculty, Federal University of Amazonas, Manaus, AM Brazil
- Physical Therapy, Speech and Occupational Therapy department, School of Medicine, University of Sao Paulo, Sao Paulo, SP Brazil
| | - Marko Ackermann
- Department of Mechanical Engineering, FEI University, Sao Bernardo do Campo, SP Brazil
| | - Jean P. Ferreira
- Department of Physical Therapy, Federal University of Sao Carlos, Sao Carlos, SP Brazil
| | | | - Isabel C. N. Sacco
- Physical Therapy, Speech and Occupational Therapy department, School of Medicine, University of Sao Paulo, Sao Paulo, SP Brazil
- Centro de Docência e Pesquisa do Departamento de Fisioterapia, Fonoaudiologia e Terapia Ocupacional, Rua Cipotânea, 51, Cidade Universitária, São Paulo, SP CEP: 05360-160 Brasil
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Effects of the lateral amplitude and regularity of upper body fluctuation on step time variability evaluated using return map analysis. PLoS One 2017; 12:e0180898. [PMID: 28700633 PMCID: PMC5507271 DOI: 10.1371/journal.pone.0180898] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2016] [Accepted: 06/22/2017] [Indexed: 11/28/2022] Open
Abstract
The aim of this study was to evaluate the effects of the lateral amplitude and regularity of upper body fluctuation on step time variability. Return map analysis was used to clarify the relationship between step time variability and a history of falling. Eleven healthy, community-dwelling older adults and twelve younger adults participated in the study. All of the subjects walked 25 m at a comfortable speed. Trunk acceleration was measured using triaxial accelerometers attached to the third lumbar vertebrae (L3) and the seventh cervical vertebrae (C7). The normalized average magnitude of acceleration, the coefficient of determination ($R^2$) of the return map, and the step time variabilities, were calculated. Cluster analysis using the average fluctuation and the regularity of C7 fluctuation identified four walking patterns in the mediolateral (ML) direction. The participants with higher fluctuation and lower regularity showed significantly greater step time variability compared with the others. Additionally, elderly participants who had fallen in the past year had higher amplitude and a lower regularity of fluctuation during walking. In conclusion, by focusing on the time evolution of each step, it is possible to understand the cause of stride and/or step time variability that is associated with a risk of falls.
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Rosati S, Agostini V, Knaflitz M, Balestra G. Muscle activation patterns during gait: A hierarchical clustering analysis. Biomed Signal Process Control 2017. [DOI: 10.1016/j.bspc.2016.09.017] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Deschamps K, Matricali GA, Desmet D, Roosen P, Keijsers N, Nobels F, Bruyninckx H, Staes F. Efficacy measures associated to a plantar pressure based classification system in diabetic foot medicine. Gait Posture 2016; 49:168-175. [PMID: 27427834 DOI: 10.1016/j.gaitpost.2016.07.009] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2015] [Revised: 06/27/2016] [Accepted: 07/07/2016] [Indexed: 02/02/2023]
Abstract
AIMS The concept of 'classification' has, similar to many other diseases, been found to be fundamental in the field of diabetic medicine. In the current study, we aimed at determining efficacy measures of a recently published plantar pressure based classification system. METHODS Technical efficacy of the classification system was investigated by applying a high resolution, pixel-level analysis on the normalized plantar pressure pedobarographic fields of the original experimental dataset consisting of 97 patients with diabetes and 33 persons without diabetes. Clinical efficacy was assessed by considering the occurence of foot ulcers at the plantar aspect of the forefoot in this dataset. Classification efficacy was assessed by determining the classification recognition rate as well as its sensitivity and specificity using cross-validation subsets of the experimental dataset together with a novel cohort of 12 patients with diabetes. RESULTS Pixel-level comparison of the four groups associated to the classification system highlighted distinct regional differences. Retrospective analysis showed the occurence of eleven foot ulcers in the experimental dataset since their gait analysis. Eight out of the eleven ulcers developed in a region of the foot which had the highest forces. Overall classification recognition rate exceeded 90% for all cross-validation subsets. Sensitivity and specificity of the four groups associated to the classification system exceeded respectively the 0.7 and 0.8 level in all cross-validation subsets. CONCLUSIONS The results of the current study support the use of the novel plantar pressure based classification system in diabetic foot medicine. It may particularly serve in communication, diagnosis and clinical decision making.
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Affiliation(s)
- Kevin Deschamps
- KU Leuven, Department of Rehabilitation Sciences, Musculoskeletal Rehabilitation Research Group, Belgium, KU Leuven, Laboratory for Clinical Motion Analysis, University Hospital Pellenberg, Belgium, Parnasse-ISEI, Department of Podiatry, Avenue E. Mounier, 84 - 1200 Bruxelles, Weligerveld 1, 3212 Pellenberg, Belgium.
| | - Giovanni Arnoldo Matricali
- KU Leuven, Department of Development & Regeneration, Belgium, KU Leuven, Multidisciplinary Diabetic Foot Clinic, University Hospitals Leuven, Belgium, Weligerveld 1, 3212 Pellenberg, Belgium.
| | - Dirk Desmet
- KU Leuven, Department of Mechanical Engineering, Belgium, Celestijnenlaan 300B bus 2420, Room 01.053, B-3001 Leuven (Heverlee), Belgium.
| | - Philip Roosen
- Department of Rehabilitation Sciences and Physiotherapy, Research Group: Musculoskeletal Rehabilitation, University Ghent, Belgium, Campus Heymans (UZ Gent), Blok B3, De Pintelaan 185, 9000 Gent.
| | - Noel Keijsers
- Sint Maartenskliniek Nijmegen, Research Department, PO box 9011, 6500 GM Nijmegen, The Netherlands.
| | - Frank Nobels
- Department of Internal Medicine- Endocrinology, Multidisciplinary Diabetic Foot Clinic, Onze-Lieve-Vrouw Ziekenhuis Aalst, Belgium, Moorselbaan 164, 9300 Aalst, Belgium.
| | - Herman Bruyninckx
- KU Leuven, Department of Mechanical Engineering, Belgium., Celestijnenlaan 300B bus 2420, room 01.053, B-3001 Leuven (Heverlee), Belgium.
| | - Filip Staes
- KU Leuven, Department of Rehabilitation Sciences-Musculoskeletal Rehabilitation Research Group, Belgium., Tervuursevest 101, B-3001 Leuven (Heverlee), Belgium.
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23
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GUIOTTO ANNAMARIA, SCARTON ALESSANDRA, SAWACHA ZIMI, GUARNERI GABRIELLA, AVOGARO ANGELO, COBELLI CLAUDIO. GAIT ANALYSIS DRIVEN 2D FINITE ELEMENT MODEL OF THE NEUROPATHIC HINDFOOT. J MECH MED BIOL 2016. [DOI: 10.1142/s0219519416500123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The diabetic foot is one of the most serious complications of diabetes mellitus and it can lead to foot ulcerations and amputations. Finite element analysis quantifies the loads developed in the different anatomical structures and describes how these affect foot tissue during foot–floor interaction. This approach for the diabetic subjects’ foot could provide valuable information in the process of plantar orthosis fabrication and fit. The purpose of this study was to develop two finite element models of the hindfoot, of healthy and diabetic neuropathic subjects. These models accounts for in vivo kinematics, kinetics, plantar pressure (PP) data and magnetic resonance images. These were acquired during gait analysis on 10 diabetic neuropathics and 10 healthy subjects. Validity of the models has been assessed through comparison between the peak PPs of simulated and experimental data: root mean square error (RMSE) in percentage of the experimental peak value was evaluated. Two different finite elements analysis were performed: subject-specific simulations in terms of both geometry and gait analysis, and by adopting the complete gait analysis dataset as boundary conditions. Model predicted plantar pressures were in good agreement with those experimentally measured. Best agreement was obtained in the subject-specific case (RMSE of 13%).
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Affiliation(s)
- ANNAMARIA GUIOTTO
- Department of Information Engineering, University of Padova, Via Gradenigo 6b, 35131 Padova, Italy
| | - ALESSANDRA SCARTON
- Department of Information Engineering, University of Padova, Via Gradenigo 6b, 35131 Padova, Italy
| | - ZIMI SAWACHA
- Department of Information Engineering, University of Padova, Via Gradenigo 6b, 35131 Padova, Italy
| | - GABRIELLA GUARNERI
- Department of Clinical Medicine and Metabolic Disease, University Polyclinic of Padova, Via Giustiniani 2, 35128 Padova, Italy
| | - ANGELO AVOGARO
- Department of Clinical Medicine and Metabolic Disease, University Polyclinic of Padova, Via Giustiniani 2, 35128 Padova, Italy
| | - CLAUDIO COBELLI
- Department of Information Engineering, University of Padova, Via Gradenigo 6b, 35131 Padova, Italy
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24
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Maksimovic A, Hanewinckel R, Verlinden VJA, Ligthart S, Hofman A, Franco OH, van Doorn PA, Tiemeier H, Dehghan A, Ikram MA. Gait characteristics in older adults with diabetes and impaired fasting glucose: The Rotterdam Study. J Diabetes Complications 2016; 30:61-6. [PMID: 26585369 DOI: 10.1016/j.jdiacomp.2015.10.006] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2015] [Revised: 10/12/2015] [Accepted: 10/13/2015] [Indexed: 11/20/2022]
Abstract
AIMS To investigate the association of diabetes mellitus and impaired fasting glucose with gait in the general middle-aged and elderly population. METHODS We performed a cross-sectional study on 3019 participants from the population-based Rotterdam Study (aged >45years, 54% women). The presence of diabetes mellitus and impaired fasting glucose was evaluated by measuring serum glucose levels and by documenting anti-diabetic treatment. Participants underwent gait analysis using an electronic walkway. Thirty gait variables were summarized into five independent gait domains for normal walking (Rhythm, Variability, Phases, Pace and Base of Support), one for turning (Turning) and one for walking heel to toe (Tandem), which were averaged into Global Gait. Linear regression analyses were performed to determine the association of diabetes, impaired fasting glucose and continuous glucose levels within the normal range with gait. RESULTS Diabetes mellitus was associated with worse Global Gait (Z-score difference -0.19, 95% confidence interval (CI) -0.30; -0.07), worse Pace (-0.20, 95% CI -0.30; -0.10) and worse Tandem (-0.21, 95% CI -0.33; -0.09), after adjusting for age, sex, height and weight. The association with Tandem remained significant after additional adjustment for cardiovascular risk factors. Impaired fasting glucose and continuous glucose levels within the normal range were not associated with any of the gait domains. CONCLUSION In our population-based study diabetes mellitus was associated with worse Global Gait, which was mostly reflected in Pace and Tandem. These associations were partly driven by other cardiovascular risk factors, emphasizing the importance of optimal control of cardiovascular risk factor profiles in patients with diabetes.
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Affiliation(s)
- Ana Maksimovic
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Rens Hanewinckel
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Neurology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | | | - Symen Ligthart
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Oscar H Franco
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Pieter A van Doorn
- Department of Neurology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Henning Tiemeier
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Psychiatry, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Abbas Dehghan
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Neurology, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Radiology, Erasmus University Medical Center, Rotterdam, the Netherlands.
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25
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Sacco ICN, Picon AP, Macedo DO, Butugan MK, Watari R, Sartor CD. Alterations in the lower limb joint moments precede the peripheral neuropathy diagnosis in diabetes patients. Diabetes Technol Ther 2015; 17:405-12. [PMID: 25664904 DOI: 10.1089/dia.2014.0284] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
BACKGROUND Changes in gait patterns in individuals with diabetes and neuropathy are still inconclusive. Our aim was to identify differences in the net intralimb moments distribution and lower limb kinematics during gait in different stage of diabetes. SUBJECTS AND METHODS This was an observational cross-sectional study that assessed 38 adults: a control group (n=12), a group with diabetes (n=12), and a group with diabetic neuropathy (n=14). The flexor and extensor joint moment peaks and kinematics of ankle, knee, and hip angles were compared among groups (by analysis of variance). RESULTS At initial contact, both diabetes groups present more hip flexion and smaller hip extensor moment. During late midstance, hip extension decreases, and flexion moment increases in both diabetes groups. For the same diabetes groups, during push off, the hip is more flexed, and the hip extensor moment decreases. Only for the diabetes group without neuropathy is the knee markedly more flexed, and the extensor moment is higher than in the other groups. At push off, the ankle is less extended in both diabetes groups, but the ankle extensor moment is significantly smaller only in neuropathic subjects. CONCLUSIONS The biomechanical modifications on the gait appeared to be a continuous process that was already revealed in patients without neuropathy. The use of the hip joint as a mechanism of forward progression of the body, instead of using the ankle, was more evident and consistent for the patients with diabetic neuropathy. The knee seems to have a major role in those with diabetes without neuropathy who presented higher extensor moments to support the body during early stance.
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Affiliation(s)
- Isabel C N Sacco
- Physical Therapy, Speech and Occupational Therapy Department, School of Medicine, University of São Paulo , São Paulo, Brazil
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26
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Amemiya A, Noguchi H, Oe M, Ohashi Y, Ueki K, Kadowaki T, Mori T, Sanada H. Elevated plantar pressure in diabetic patients and its relationship with their gait features. Gait Posture 2014; 40:408-14. [PMID: 24974127 DOI: 10.1016/j.gaitpost.2014.05.063] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2013] [Revised: 05/21/2014] [Accepted: 05/23/2014] [Indexed: 02/02/2023]
Abstract
PURPOSE High plantar pressure is a major risk factor for diabetic foot ulcers. The relationship between plantar pressure and foot mobility has been investigated in some studies. However, when the foot is in motion, foot mobility is only a small feature of the gait. Therefore, we investigated relationship between high plantar pressure and gait and also studied the motion of the trunk. In addition, we investigated the relationship between gait and patient characteristics to identify patients at high-risk of developing diabetic foot ulcers. METHODS The relationships between elevated plantar pressure, gait features, and patient characteristics were analyzed. Plantar pressure distribution in the stance phase was divided on the four plantar segments. Elevated plantar pressure was defined as being more than the mean plus one standard deviation of the corresponding segment in non-diabetic subjects. Plantar pressure distribution was measured by an F-scan system, and gait features were measured using wireless motion sensors attached to the sacrum and feet. Patient characteristics were obtained from medical records or by interview. RESULTS Small roll and yaw motions of the body and yaw motion of the foot during the mid-stance phase were related to the elevated plantar pressure in 57 diabetic patients. Furthermore, these gait features were related to sensory neuropathy, diabetes duration, patient weight, toe-gap force, and ankle range of motion. CONCLUSION Given our findings, it may be possible to prevent diabetic foot ulcers by increasing foot motion during the mid-stance phase. Passive exercise aimed at expanding ankle range of motion in patients with sensory neuropathy or long-standing diabetes may assist in achieving this.
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Affiliation(s)
- Ayumi Amemiya
- The University of Tokyo, Department of Wound Care Management, Graduate School of Medicine, Japan
| | - Hiroshi Noguchi
- The University of Tokyo, Department of Life Support Technology (Molten), Graduate School of Medicine, Japan
| | - Makoto Oe
- The University of Tokyo, Department of Advanced Nursing Technology, Graduate School of Medicine, Japan
| | - Yumiko Ohashi
- The University of Tokyo Hospital, Department of Nursing, Japan
| | - Kohjiro Ueki
- The University of Tokyo, Department of Diabetes and Metabolic Diseases, Japan
| | - Takashi Kadowaki
- The University of Tokyo, Department of Diabetes and Metabolic Diseases, Japan
| | - Taketoshi Mori
- The University of Tokyo, Department of Life Support Technology (Molten), Graduate School of Medicine, Japan.
| | - Hiromi Sanada
- The University of Tokyo, Department of Wound Care Management, Graduate School of Medicine, Japan
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27
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Deschamps K, Matricali GA, Roosen P, Desloovere K, Bruyninckx H, Spaepen P, Nobels F, Tits J, Flour M, Staes F. Classification of forefoot plantar pressure distribution in persons with diabetes: a novel perspective for the mechanical management of diabetic foot? PLoS One 2013; 8:e79924. [PMID: 24278219 PMCID: PMC3838415 DOI: 10.1371/journal.pone.0079924] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2013] [Accepted: 09/29/2013] [Indexed: 12/20/2022] Open
Abstract
Background The aim of this study was to identify groups of subjects with similar patterns of forefoot loading and verify if specific groups of patients with diabetes could be isolated from non-diabetics. Methodology/Principal Findings Ninety-seven patients with diabetes and 33 control participants between 45 and 70 years were prospectively recruited in two Belgian Diabetic Foot Clinics. Barefoot plantar pressure measurements were recorded and subsequently analysed using a semi-automatic total mapping technique. Kmeans cluster analysis was applied on relative regional impulses of six forefoot segments in order to pursue a classification for the control group separately, the diabetic group separately and both groups together. Cluster analysis led to identification of three distinct groups when considering only the control group. For the diabetic group, and the computation considering both groups together, four distinct groups were isolated. Compared to the cluster analysis of the control group an additional forefoot loading pattern was identified. This group comprised diabetic feet only. The relevance of the reported clusters was supported by ANOVA statistics indicating significant differences between different regions of interest and different clusters. Conclusion/s Significance There seems to emerge a new era in diabetic foot medicine which embraces the classification of diabetic patients according to their biomechanical profile. Classification of the plantar pressure distribution has the potential to provide a means to determine mechanical interventions for the prevention and/or treatment of the diabetic foot.
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Affiliation(s)
- Kevin Deschamps
- Department of Rehabilitation Sciences, Katholieke Universiteit Leuven, Leuven, Belgium
- Laboratory for Clinical Motion Analysis, University Hospitals Leuven, Pellenberg, Belgium
- Multidisciplinary Diabetic Foot Clinic, University Hospitals Leuven, Leuven, Belgium
- * E-mail:
| | - Giovanni Arnoldo Matricali
- Multidisciplinary Diabetic Foot Clinic, University Hospitals Leuven, Leuven, Belgium
- Department of Development & Regeneration, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Philip Roosen
- Department of Rehabilitation Sciences, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Kaat Desloovere
- Department of Rehabilitation Sciences, Katholieke Universiteit Leuven, Leuven, Belgium
- Laboratory for Clinical Motion Analysis, University Hospitals Leuven, Pellenberg, Belgium
| | - Herman Bruyninckx
- Department of Mechanical Engineering, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Pieter Spaepen
- Department of Mechanical Engineering, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Frank Nobels
- Department of Internal Medicine- Endocrinology, Onze-Lieve-Vrouw Ziekenhuis Aalst, Aalst, Belgium
| | - Jos Tits
- Department of Internal Medicine- Endocrinology, Onze-Lieve-Vrouw Ziekenhuis Aalst, Aalst, Belgium
| | - Mieke Flour
- Multidisciplinary Diabetic Foot Clinic, University Hospitals Leuven, Leuven, Belgium
- Department of Dermatology, University Hospitals Leuven, Leuven, Belgium
| | - Filip Staes
- Department of Rehabilitation Sciences, Katholieke Universiteit Leuven, Leuven, Belgium
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28
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Laudani L, Vannozzi G, Sawacha Z, della Croce U, Cereatti A, Macaluso A. Association between physical activity levels and physiological factors underlying mobility in young, middle-aged and older individuals living in a city district. PLoS One 2013; 8:e74227. [PMID: 24040209 PMCID: PMC3765304 DOI: 10.1371/journal.pone.0074227] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2013] [Accepted: 07/29/2013] [Indexed: 12/13/2022] Open
Abstract
Maintaining adequate levels of physical activity is known to preserve health status and functional independence as individuals grow older. However, the relationship between determinants of physical activity (volume and intensity) and physiological factors underlying mobility (cardio-respiratory fitness, neuromuscular function and functional abilities) is still unclear. The aim of this study was to investigate the association between objectively quantified physical activity and a spectrum of physiological factors underlying mobility in young, middle-aged and older individuals living in a city district. Experiments were carried out on 24 young (28 ± 2 years), 24 middle-aged (48 ± 2 years) and 24 older (70 ± 3 years) gender-matched volunteers. Physical activity was monitored by a wearable activity monitor to quantify volume and intensity of overall physical activity and selected habitual activities over 24 hours. Ventilatory threshold was assessed during an incremental cycling test. Torque, muscle fiber conduction velocity and agonist-antagonist coactivation were measured during maximal voluntary contraction of knee extensors and flexors. Ground reaction forces were measured during sit-to-stand and counter-movement jump. K-means cluster analysis was used to classify the participants' physical activity levels based on parameters of volume and intensity. Two clusters of physical activity volume (i.e., high and low volume) and three clusters of physical activity intensity (i.e. high, medium and low intensity) were identified in all participants. Cardio-respiratory fitness was associated with volume of overall physical activity as well as lying, sitting, standing, walking and stair climbing. On the other hand, neuromuscular function and functional abilities showed a significant association with intensity of overall physical activity as well as postural transition, walking and stair climbing. As a practical application, the relative role played by volume and intensity of overall physical activity and selected habitual activities should be taken into account in the design of preventative training interventions to preserve mobility as individuals grow older.
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Affiliation(s)
- Luca Laudani
- Department of Human Movement, Social and Health Sciences, University of Rome Foro Italico, Rome, Italy
| | - Giuseppe Vannozzi
- Department of Human Movement, Social and Health Sciences, University of Rome Foro Italico, Rome, Italy
| | - Zimi Sawacha
- Department of Information Engineering, University of Padua, Padua, Italy
| | - Ugo della Croce
- Information Engineering Unit, Department of POLCOMING, University of Sassari, Sassari, Italy
| | - Andrea Cereatti
- Information Engineering Unit, Department of POLCOMING, University of Sassari, Sassari, Italy
| | - Andrea Macaluso
- Department of Human Movement, Social and Health Sciences, University of Rome Foro Italico, Rome, Italy
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29
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Abstract
An article by Ferber and coauthors in Journal of Diabetes Science and Technology reported on the ability of a novel in-shoe plantar sensory replacement unit (PSRU) to provide alert-based feedback derived from analyzing plantar pressure (PP) threshold measurements in real time. The study aimed at comparing the PSRU device to a gold standard pressure-sensing device (GS-PSD) to determine the correlation between concurrent measures of PP during walking. Data were collected simultaneously from 10 participants who walked overground with both devices. The variable of interest was the number of recorded data points greater than 32 mmHg for each of the PSRU sensors and corresponding average recordings from the GS-PSD. Authors concluded that the PSRU provides analogous data to the GS-PSD. However, several aspects of the study should be considered when interpreting their clinical relevance.
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Affiliation(s)
- Zimi Sawacha
- Department of Information Engineering, University of Padova, Via Gradenigo 6b I, 35131 Padova, Italy.
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30
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Kelly C, Fleischer A, Yalla S, Grewal GS, Albright R, Berns D, Crews R, Najafi B. Fear of falling is prevalent in older adults with diabetes mellitus but is unrelated to level of neuropathy. J Am Podiatr Med Assoc 2013; 103:480-8. [PMID: 24297984 PMCID: PMC4732269 DOI: 10.7547/1030480] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
BACKGROUND Patients with diabetic peripheral neuropathy (DPN) demonstrate gait alterations compared with their nonneuropathic counterparts, which may place them at increased risk for falling. However, it is uncertain whether patients with DPN also have a greater fear of falling. METHODS A voluntary group of older adults with diabetes was asked to complete a validated fear of falling questionnaire (Falls Efficacy Scale International [FES-I]) and instructed to walk 20 m in their habitual shoes at their habitual speed. Spatiotemporal parameters of gait (eg, stride velocity and gait speed variability) were collected using a validated body-worn sensor technology. Balance during walking was also assessed using sacral motion in the mediolateral and anteroposterior directions. The level of DPN was quantified using vibration perception threshold from the great toe. RESULTS Thirty-four diabetic patients (mean ± SD: age, 67.6 ± 9.2 years; body mass index, 30.9 ± 5.7; hemoglobin A1c, 7.9% ± 2.3%) with varying levels of neuropathy (mean ± SD vibration perception threshold, 34.6 ± 22.9 V) were recruited. Most participants (28 of 34, 82%) demonstrated moderate to high concern about falling based on their FES-I score. Age (r = 0.6), hemoglobin A1c level (r = 0.39), number of steps required to reach steady-state walking (ie, gait initiation) (r = 0.4), and duration of double support (r = 0.44) were each positively correlated with neuropathy severity (P < .05). Participants with a greater fear of falling also walked with slower stride velocities and shorter stride lengths (r = -0.3 for both, P < .05). However, no correlation was observed between level of DPN and the participant's actual concern about falling. CONCLUSIONS Fear of falling is prevalent in older adults with diabetes mellitus but is unrelated to level of neuropathy.
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Affiliation(s)
- Carolyn Kelly
- Advocate Illinois Masonic Medical Center, Chicago, IL
| | - Adam Fleischer
- Center for Lower Extremity Ambulatory Research, Dr. William M. Scholl College of Podiatric Medicine at Rosalind Franklin University of Medicine and Science, North Chicago, IL
| | - Sai Yalla
- Center for Lower Extremity Ambulatory Research, Dr. William M. Scholl College of Podiatric Medicine at Rosalind Franklin University of Medicine and Science, North Chicago, IL
| | - Gurtej S. Grewal
- Southern Arizona Limb Salvage Alliance, Department of Surgery and Interdisciplinary Consortium on Advanced Motion Performance, Arizona Center on Aging, University of Arizona College of Medicine, Tucson, AZ
| | - Rachel Albright
- Center for Lower Extremity Ambulatory Research, Dr. William M. Scholl College of Podiatric Medicine at Rosalind Franklin University of Medicine and Science, North Chicago, IL
| | - Dana Berns
- Center for Lower Extremity Ambulatory Research, Dr. William M. Scholl College of Podiatric Medicine at Rosalind Franklin University of Medicine and Science, North Chicago, IL
| | - Ryan Crews
- Center for Lower Extremity Ambulatory Research, Dr. William M. Scholl College of Podiatric Medicine at Rosalind Franklin University of Medicine and Science, North Chicago, IL
| | - Bijan Najafi
- Southern Arizona Limb Salvage Alliance, Department of Surgery and Interdisciplinary Consortium on Advanced Motion Performance, Arizona Center on Aging, University of Arizona College of Medicine, Tucson, AZ
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31
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Lee JU, Kim JH, Lee LK, Kim MY, Yang SM, Lee TH, Kim J. Posture Analysis of Various Types of Crutch Gait of Healthy Volunteers. J Phys Ther Sci 2013. [DOI: 10.1589/jpts.25.453] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Affiliation(s)
- Jeong-Uk Lee
- Laboratory of Health Science and Nanophysiotherapy, Department of Physical Therapy, Graduate School, Yongin University
| | - Ju-Hyun Kim
- Laboratory of Health Science and Nanophysiotherapy, Department of Physical Therapy, Graduate School, Yongin University
| | - Lim-Kyu Lee
- Laboratory of Health Science and Nanophysiotherapy, Department of Physical Therapy, Graduate School, Yongin University
| | - Mee-Young Kim
- Laboratory of Health Science and Nanophysiotherapy, Department of Physical Therapy, Graduate School, Yongin University
| | - Seung-Min Yang
- Laboratory of Health Science and Nanophysiotherapy, Department of Physical Therapy, Graduate School, Yongin University
| | - Tae-Hyun Lee
- Department of Combative Martial Arts Training, College of Martial Arts, Yongin University
| | - Junghwan Kim
- Department of Physical Therapy, College of Public Health and Welfare, Yongin University: Yongin 449-714, Korea
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32
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Bennetts CJ, Owings TM, Erdemir A, Botek G, Cavanagh PR. Clustering and classification of regional peak plantar pressures of diabetic feet. J Biomech 2012; 46:19-25. [PMID: 23089457 DOI: 10.1016/j.jbiomech.2012.09.007] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2012] [Revised: 08/09/2012] [Accepted: 09/07/2012] [Indexed: 12/01/2022]
Abstract
High plantar pressures have been associated with foot ulceration in people with diabetes, who can experience loss of protective sensation due to peripheral neuropathy. Therefore, characterization of elevated plantar pressure distributions can provide a means of identifying diabetic patients at potential risk of foot ulceration. Plantar pressure distribution classification can also be used to determine suitable preventive interventions, such as the provision of an appropriately designed insole. In the past, emphasis has primarily been placed on the identification of individual focal areas of elevated pressure. The goal of this study was to utilize k-means clustering analysis to identify typical regional peak plantar pressure distributions in a group of 819 diabetic feet. The number of clusters was varied from 2 to 10 to examine the effect on the differentiation and classification of regional peak plantar pressure distributions. As the number of groups increased, so too did the specificity of their pressure distributions: starting with overall low or overall high peak pressure groups and extending to clusters exhibiting several focal peak pressures in different regions of the foot. However, as the number of clusters increased, the ability to accurately classify a given regional peak plantar pressure distribution decreased. The balance between these opposing constraints can be adjusted when assessing patients with feet that are potentially "at risk" or while prescribing footwear to reduce high regional pressures. This analysis provides an understanding of the variability of the regional peak plantar pressure distributions seen within the diabetic population and serves as a guide for the preemptive assessment and prevention of diabetic foot ulcers.
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Affiliation(s)
- Craig J Bennetts
- Department of Biomedical Engineering, Cleveland Clinic, Cleveland, OH 44195, USA
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