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Licensed Unlicensed Requires Authentication Published by De Gruyter November 17, 2016

Application of DCT-derived parameters for early detection of polyneuropathy in diabetic patients

  • Damian Dzienniak EMAIL logo and Jacek Cieślik

Abstract

Diabetic foot is one of the most severe complications of diabetes. Early diagnosis of this syndrome can ensure proper medical care and adequate treatment. Various image analysis methods can be used to speed up the diagnosis process, and automated diagnosis can be applied as a screening technique to reduce its cost. Introducing auxiliary diagnostic parameters may help to detect polyneuropathy or neuropathy, both of which often precede the appearance of diabetic foot syndrome. The present paper describes a study performed on a group of diabetic patients by analyzing plantar pressure distribution images. As part of this study, 2D discrete cosine transform (DCT) is computed for the forefoot and rearfoot regions of each diabetic subject in a group of 37 patients. Three new DCT-based parameters are introduced to help to detect polyneuropathy or at least indicate that the patient may have polyneuropathy without a time-consuming examination. The results indicate a certain relationship between these parameters and the presence of polyneuropathy. This information could be used in further diagnosis to prevent foot ulcers from developing in patients with diabetes.

  1. Author contributions: The authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Employment or leadership: None declared.

  4. Honorarium: None declared.

  5. Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

References

1. Singh N, Armstrong DG, Lipsky BA. Preventing foot ulcers in patients with diabetes. J Am Med Assoc 2005;293:217–28.10.1001/jama.293.2.217Search in Google Scholar

2. Clarke A. Avoiding foot complications in diabetes: foot complications in diabetes are serious and costly. CME 2010;28:181–5.Search in Google Scholar

3. Weigelt JA, editor. MRSA. 2nd ed. New York: Informa Healthcare, 2010.Search in Google Scholar

4. Motley TA, Gilligan AM, Lange DL, Waycaster CR, Dickerson Jr JE. Cost-effectiveness of clostridial collagenase ointment on wound closure in patients with diabetic foot ulcers: economic analysis of results from a multicenter, randomized, open-label trial. J Foot Ankle Res 2015;8:7.10.1186/s13047-015-0065-xSearch in Google Scholar

5. Delbridge L, Ctercteko G, Fowler C, Reeve TS, Le Quesne LP. The aetiology of diabetic neuropathic ulceration of the foot. Br J Surg 1985;72:1–6.10.1002/bjs.1800720102Search in Google Scholar

6. Caselli A, Pham H, Giurini JM, Armstrong DG, Veves A. The forefoot-to-rearfoot plantar pressure ratio is increased in severe diabetic neuropathy and can predict foot ulceration. Diabetes Care 2002;25:1066–71.10.2337/diacare.25.6.1066Search in Google Scholar

7. Boulton AJ. Pressure and the diabetic foot: clinical science and offloading techniques. Am J Surg 2004;187:17S–24S.10.1016/S0002-9610(03)00297-6Search in Google Scholar

8. Boulton AJ, Vinik AI, Arezzo JC, Bril V, Feldman EL, Freeman R, et al. Diabetic neuropathies: a statement by the American Diabetes Association. Diabetes Care 2005;28:956–62.10.2337/diacare.28.4.956Search in Google Scholar PubMed

9. Alexiadou K, Doupis J. Management of diabetic foot ulcers. Diabetes Ther 2012;3:4.10.1007/s13300-012-0004-9Search in Google Scholar PubMed PubMed Central

10. Prabhu KG, Patil KM, Srinivasan S. Diabetic feet at risk: a new method of analysis of walking foot pressure images at different levels of neuropathy for early detection of plantar ulcers. Med Biol Eng Comput 2001;39:288–93.10.1007/BF02345282Search in Google Scholar PubMed

11. Charanya G, Patil KM, Thomas JV, Narayanamurthy VB, Parivalavan R, Visvanath K. Standing foot pressure image analysis for variations in foot sole soft tissue properties and levels of diabetic neuropathy. ITBM-RBM 2004;25:23–33.10.1016/j.rbmret.2003.11.002Search in Google Scholar

12. Acharya UR, Tan PH, Subramaniam T, Tamura T, Chua KC, Goh SC, et al. Automated identification of diabetic type 2 subjects with and without neuropathy using wavelet transform on pedobarograph. J Med Syst 2007;32:21–9.10.1007/s10916-007-9103-ySearch in Google Scholar PubMed

13. Periyasamy R, Mishra A, Anand S, Ammini AC. Preliminary investigation of foot pressure distribution variation in men and women adults while standing. Foot 2011;21:142–8.10.1016/j.foot.2011.03.001Search in Google Scholar PubMed

14. Siddiqui HR, Spruce M, Alty SR, Dudley S. Automated peripheral neuropathy assessment using optical imaging and foot anthropometry. IEEE Trans Biomed Eng 2015;62:1911–7.10.1109/TBME.2015.2407056Search in Google Scholar PubMed

15. Keijsers NL, Stolwijk NM, Pataky TC. Linear dependence of peak, mean, and pressure-time integral values in plantar pressure images. Gait Posture 2010;31:140–2.10.1016/j.gaitpost.2009.08.248Search in Google Scholar PubMed

16. Razjouyan J, Khayat O, Siahi M, Mansouri AA. A hybrid soft-computing method for image analysis of digital plantar scanners. J Med Signals Sensors 2013;3:15–21.10.4103/2228-7477.114304Search in Google Scholar

17. Grabara M. Influence of football training on alignment of the lower limbs and shaping of the feet. Hum Move 2008;9:46–50.10.2478/v10038-008-0007-6Search in Google Scholar

18. Shah SR, Patil KM. Processing of foot pressure images and display of an advanced clinical parameter PR in diabetic neuropathy. In: Proceedings of the 2nd International IEEE EMBS Conference on Neural Engineering, Arlington, VA, 2005.Search in Google Scholar

19. Puri M, Patil KM, Balasubramanian V, Narayanamurthy VB. Texture analysis of foot sole soft tissue images in diabetic neuropathy using wavelet transform. Med Biol Eng Comput 2005;43:756–63.10.1007/BF02430954Search in Google Scholar PubMed

20. Prabhu KG, Patil KM, Srinivasan S. A new method of analysis of standing foot pressure images for detection of the plantar ulcers in early-stage diabetic neuropathy. Front Med Biol Eng 2000;11:31–43.10.1163/156855701750383178Search in Google Scholar PubMed

21. Golec J, Gołaszewska K, Kamińska M, Szczygieł E, Golec P, Tomaszewski P. Evaluation of disorder of balance and posture in the osteoarthrosis and osteoporosis. Ostry Dyżur 2015;8:170–4.Search in Google Scholar

22. Chen S, An T, Hao L. Discrete cosine transform image compression based on genetic algorithm. In: International Conference on Information Engineering and Computer Science, Wuhan, 2009:1–3.10.1109/ICIECS.2009.5364273Search in Google Scholar

23. Downey AB. Think DSP: digital signal processing in Python. Needham, MA: Green Tea Press, 2014.Search in Google Scholar

24. Makhoul J. A fast cosine transform in one and two dimensions. IEEE Trans Acoust Speech Signal Proc 1980;28:27–34.10.1109/TASSP.1980.1163351Search in Google Scholar

25. Mueller MJ, Zou D, Lott DJ. “Pressure gradient” as an indicator of plantar skin injury. Diabetes Care 2005;28:2908–12.10.2337/diacare.28.12.2908Search in Google Scholar PubMed

26. Mueller MJ, Zou D, Lott DJ. Pressure gradient and subsurface shear stress on the neuropathic forefoot. Clin Biomech 2008;23:342–8.10.1016/j.clinbiomech.2007.10.005Search in Google Scholar PubMed PubMed Central

Received: 2016-9-6
Accepted: 2016-10-24
Published Online: 2016-11-17
Published in Print: 2016-12-1

©2016 Walter de Gruyter GmbH, Berlin/Boston

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