ABSTRACT
Machine learning is a superior tool that is unbiased and moderately comparable to the medical expert in making medical diagnostics if trained with correct supervision. In this paper we developed a supervised learning algorithm employing plantar pressure data to detect the anomaly called hallux valgus (HV) on a number of subject. Support vector machine (SVM) and its variants such as kernel SVM and ensemble SVM were evaluated on a plantar pressure open dataset. Results show that SVMs in general have the average classification rate of above 90 percent.
- Brian G. Booth, Noel L.W. Keijsers, Toon Huysmans, and Jan Sijbers. 2019. The CAD WALK Hallux Valgus Dataset (Pre-Surgery). https://doi.org/10.5281/zenodo.3406523 This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska- Curie grant agreement No 746614..Google Scholar
- Leo Breiman. 1996. Bagging predictors. Machine learning 24, 2 (1996), 123–140.Google Scholar
- Sicco A Bus and Antony de Lange. 2005. A comparison of the 1-step, 2-step, and 3-step protocols for obtaining barefoot plantar pressure data in the diabetic neuropathic foot. Clinical biomechanics 20, 9 (2005), 892–899.Google Scholar
- PR Cavanagh and JS Ulbrecht. 1994. Clinical plantar pressure measurement in diabetes: rationale and methodology. The foot 4, 3 (1994), 123–135.Google Scholar
- Bavornrit Chuckpaiwong, James A Nunley, Nathan A Mall, and Robin M Queen. 2008. The effect of foot type on in-shoe plantar pressure during walking and running. Gait & posture 28, 3 (2008), 405–411.Google Scholar
- Corinna Cortes and Vladimir Vapnik. 1995. Support-Vector Networks. In Machine Learning. 273–297.Google Scholar
- John P Cunningham and Zoubin Ghahramani. 2015. Linear dimensionality reduction: Survey, insights, and generalizations. The Journal of Machine Learning Research 16, 1 (2015), 2859–2900.Google ScholarDigital Library
- Malindu Fernando, Robert Crowther, Peter Lazzarini, Kunwarjit Sangla, Margaret Cunningham, Petra Buttner, and Jonathan Golledge. 2013. Biomechanical characteristics of peripheral diabetic neuropathy: A systematic review and meta-analysis of findings from the gait cycle, muscle activity and dynamic barefoot plantar pressure. Clinical biomechanics 28, 8 (2013), 831–845.Google Scholar
- Saeed Forghany, Christopher Nester, Sarah Tyson, Stephen Preece, and Richard Jones. 2019. Plantar pressure distribution in people with stroke and association with functional mobility. Journal of Rehabilitation Sciences & Research 6, 2 (2019), 80–85.Google Scholar
- Yoav Freund and Robert E Schapire. 1997. A decision-theoretic generalization of on-line learning and an application to boosting. Journal of computer and system sciences 55, 1 (1997), 119–139.Google ScholarDigital Library
- Hyo-Seon Jeon, Jonghee Han, Won-Jin Yi, BeomSeok Jeon, and Kwang Suk Park. 2008. Classification of Parkinson gait and normal gait using spatial-temporal image of plantar pressure. In 2008 30th annual international conference of the ieee engineering in medicine and biology society. IEEE, 4672–4675.Google Scholar
- Muge Kirmizi, Yesim S Sengul, and Salih Angin. 2020. The effects of gait speed on plantar pressure variables in individuals with normal foot posture and flatfoot. Acta Bioeng. Biomech 22, 3 (2020), 161–168.Google ScholarCross Ref
- Lawrence A Lavery, David G Armstrong, Robert P Wunderlich, Jeffrey Tredwell, and Andrew JM Boulton. 2003. Predictive value of foot pressure assessment as part of a population-based diabetes disease management program. Diabetes care 26, 4 (2003), 1069–1073.Google ScholarCross Ref
- Christina Zong-Hao Ma, Yong-Ping Zheng, and Winson Chiu-Chun Lee. 2018. Changes in gait and plantar foot loading upon using vibrotactile wearable biofeedback system in patients with stroke. Topics in stroke rehabilitation 25, 1 (2018), 20–27.Google Scholar
- Katrina S Maluf, Robert E Morley Jr, Edward J Richter, Joseph W Klaesner, and Michael J Mueller. 2004. Foot pressures during level walking are strongly associated with pressures during other ambulatory activities in subjects with diabetic neuropathy. Archives of physical medicine and rehabilitation 85, 2(2004), 253–260.Google Scholar
- National Institute of Health. 2013. Neuroimaging Informatics Technology Initiative. Retrieved August 1, 2022 from https://nifti.nimh.nih.gov/Google Scholar
- Ryuhei Okuno, Satoshi Fujimoto, Jun Akazawa, Masaru Yokoe, Saburo Sakoda, and Kenzo Akazawa. 2008. Analysis of spatial temporal plantar pressure pattern during gait in Parkinson’s disease. In 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 1765–1768.Google ScholarCross Ref
- Gaurav Shalin, Scott Pardoel, Edward D Lemaire, Julie Nantel, and Jonathan Kofman. 2021. Prediction and detection of freezing of gait in Parkinson’s disease from plantar pressure data using long short-term memory neural-networks. Journal of neuroengineering and rehabilitation 18, 1(2021), 1–15.Google ScholarCross Ref
- Gaurav Shalin, Scott Pardoel, Julie Nantel, Edward D Lemaire, and Jonathan Kofman. 2020. Prediction of freezing of gait in Parkinson’s disease from foot plantar-pressure arrays using a convolutional neural network. In 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 244–247.Google ScholarCross Ref
- Joyce AC van Tunen, Kade L Paterson, Tim V Wrigley, Ben R Metcalf, Jonas B Thorlund, and Rana S Hinman. 2018. Effect of knee unloading shoes on regional plantar forces in people with symptomatic knee osteoarthritis–an exploratory study. Journal of Foot and Ankle Research 11, 1 (2018), 1–8.Google ScholarCross Ref
- Mo Wang, Zhuochen Fan, Fei Chen, Sixu Zhang, Chen Peng, 2019. Research on feature extraction algorithm for plantar pressure image and gait analysis in stroke patients. Journal of Visual Communication and Image Representation 58 (2019), 525–531.Google ScholarCross Ref
- Zhiwang Zhang, Lin Wang, Kaijun Hu, and Yu Liu. 2017. Characteristics of plantar loads during walking in patients with knee osteoarthritis. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research 23(2017), 5714.Google Scholar
Index Terms
- Anomaly Detection of Hallux Valgus using Plantar Pressure Data
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