title: Objectively quantifying walking ability in degenerative spinal disorder patients using sensor equipped smart shoes.
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.
authors.affiliation: Department of Physical Medicine & Rehabilitation, Harvard Medical School, Charlestown, MA 02129, USA; Spaulding Rehabilitation Hospital, Charlestown, MA 02129, USA; Computer Science Department, UCLA, Los Angeles, CA 90095, USA; Wireless Health Institute, UCLA, Los Angeles, CA 90095, USA. Electronic address: slee117@partners.org.
authors.forename: Sunghoon Ivan
authors.initials: SI
authors.lastname: Lee
authors.affiliation: Computer Science Department, UCLA, Los Angeles, CA 90095, USA; Wireless Health Institute, UCLA, Los Angeles, CA 90095, USA. Electronic address: ejpark@cs.ucla.edu.
authors.forename: Eunjeong
authors.initials: E
authors.lastname: Park
authors.affiliation: Department of Neurosurgery, UCLA, Los Angeles, CA 90095, USA. Electronic address: ahuang@mednet.ucla.edu.
authors.forename: Alex
authors.initials: A
authors.lastname: Huang
authors.affiliation: Computer Science Department, UCLA, Los Angeles, CA 90095, USA; Wireless Health Institute, UCLA, Los Angeles, CA 90095, USA; Center for Outcomes Research and Evaluation, Yale School of Medicine, New Haven, CT 06510, USA. Electronic address: bobak.mortazavi@yale.edu.
authors.forename: Bobak
authors.initials: B
authors.lastname: Mortazavi
authors.affiliation: Department of Neurosurgery, UCLA, Los Angeles, CA 90095, USA. Electronic address: jgarst@mednet.ucla.edu.
authors.forename: Jordan Hayward
authors.initials: JH
authors.lastname: Garst
authors.affiliation: Department of Neurosurgery, UCLA, Los Angeles, CA 90095, USA.
authors.forename: Nima
authors.initials: N
authors.lastname: Jahanforouz
authors.affiliation: Department of Neurosurgery, UCLA, Los Angeles, CA 90095, USA.
authors.forename: Marie
authors.initials: M
authors.lastname: Espinal
authors.affiliation: Department of Neurosurgery, UCLA, Los Angeles, CA 90095, USA.
authors.forename: Tiffany
authors.initials: T
authors.lastname: Siero
authors.affiliation: Department of Neurosurgery, UCLA, Los Angeles, CA 90095, USA.
authors.forename: Sophie
authors.initials: S
authors.lastname: Pollack
authors.affiliation: Department of Neurosurgery, UCLA, Los Angeles, CA 90095, USA.
authors.forename: Marwa
authors.initials: M
authors.lastname: Afridi
authors.affiliation: Department of Neurosurgery, UCLA, Los Angeles, CA 90095, USA.
authors.forename: Meelod
authors.initials: M
authors.lastname: Daneshvar
authors.affiliation: Department of Neurosurgery, UCLA, Los Angeles, CA 90095, USA.
authors.forename: Saif
authors.initials: S
authors.lastname: Ghias
authors.affiliation: Department of Neurosurgery, UCLA, Los Angeles, CA 90095, USA; Neuroplasticity and Repair Laboratory, UCLA, Los Angeles, CA 90095, USA; Neuromotor Recovery and Rehabilitation Center, UCLA, Los Angeles, CA 90095, USA; Department of Orthopaedic Surgery, UCLA, Los Angeles, CA 90095, USA. Electronic address: dclu@mednet.ucla.edu.
authors.forename: Daniel C
authors.initials: DC
authors.lastname: Lu
authors.affiliation: Computer Science Department, UCLA, Los Angeles, CA 90095, USA; Wireless Health Institute, UCLA, Los Angeles, CA 90095, USA. Electronic address: majid@cs.ucla.edu.
authors.forename: Majid
authors.initials: M
authors.lastname: Sarrafzadeh
mesh_terms: D000328:Adult; D000368:Aged; D005260:Female; D005684:Gait; D006801:Humans; D008159:Lumbar Vertebrae / Q000503:physiopathology / Q000601:surgery; D000069550:Machine Learning; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic / Q000295:instrumentation*; D011184:Postoperative Period; D057234:Preoperative Period; D011312:Pressure; D012775:Shoes; D062211:Spatio-Temporal Analysis; D013130:Spinal Stenosis / Q000503:physiopathology* / Q000601:surgery; D016138:Walking
keywords: Functional level; Lumbar spinal stenosis; Pressure mapping; Self-paced walking test; Smart shoes; Spinal cord disorder; Walking ability