Objectively quantifying walking ability in degenerative spinal disorder patients using sensor equipped smart shoes. Issue 5 (May 2016)

• Record Type: Journal Article
• Authors: Lee, Sunghoon Ivan; Park, Eunjeong; Huang, Alex; Mortazavi, Bobak; Hayward Garst, Jordan; Jahanforouz, Nima; Espinal, Marie; Siero, Tiffany; Pollack, Sophie; Afridi, Marwa; Daneshvar, Meelod; Ghias, Saif; C. Lu, Daniel; Sarrafzadeh, Majid
• Is Part Of: Medical engineering & physics. Volume 38:Issue 5(2016:May)
• Page Start: 442
• Page End: 449
• Publication Date: 2016-05
• Subjects: Lumbar spinal stenosis -- Spinal cord disorder -- Self-paced walking test -- Pressure mapping -- Smart shoes -- Functional level -- Walking ability; Biomedical engineering -- Periodicals; Biomedical Engineering -- Periodicals; Physics -- Periodicals; Génie biomédical -- Périodiques; Biomedical engineering; Electronic journals; Periodicals; 610.28
• DOI: 10.1016/j.medengphy.2016.02.004
• Languages: English
• ISSNs: 1350-4533

Abstract

Highlights: The functional level of LSS patients is quantified using a pair of sensorized shoes. Machine learning algorithms were used to estimate the Oswestry Disability Index. The functional level can be accurately quantified by analyzing walking ability. Abstract: Lumbar spinal stenosis (LSS) is a condition associated with the degeneration of spinal disks in the lower back. A significant majority of the elderly population experiences LSS, and the number is expected to grow. The primary objective of medical treatment for LSS patients has focused on improving functional outcomes (e.g., walking ability) and thus, an accurate, objective, and inexpensive method to evaluate patients' functional levels is in great need. This paper aims to quantify the functional level of LSS patients by analyzing their clinical information and their walking ability from a 10 m self-paced walking test using a pair of sensorized shoes. Machine learning algorithms were used to estimate the Oswestry Disability Index, a clinically well-established functional outcome, from a total of 29 LSS patients. The estimated ODI scores showed a significant correlation to the reported ODI scores with a Pearson correlation coefficient ( r ) of 0.81 and p < 3.5 × 10 − 11 . It was further shown that the data extracted from the sensorized shoes contribute most to the reported estimation results, and that the contribution of the clinical information was minimal. This study enables new research and clinical opportunities for monitoring the functional level of LSS patients in hospital and ambulatory settings.