ArticleMedical engineering & physics2016
Objectively quantifying walking ability in degenerative spinal disorder patients using sensor equipped smart shoes.
Article in Medical engineering & physics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it, 41 citations in OpenAlex.
- Utility of machine learning algorithms in degenerative cervical and lumbar spine disease: a systematic review.Neurosurgical review · 2022Pooled it
- Artificial Intelligence Technologies in Neurosurgery: a Systematic Literature Review Using Topic Modeling. Part II: Research Objectives and Perspectives.Sovremennye tekhnologii v meditsine · 2021Pooled it
- Objective physical performance and exercise tests of patients with lumbar spinal stenosis: a systematic scoping review.BMC sports science, medicine & rehabilitation · 2026Article
- Wearable sensor technologies for individuals with back pain: a scoping review.Pain management · 2025Article
- Application of Carbon Nanotube-Based Elastomeric Matrix for Capacitive Sensing in Diabetic Foot Orthotics.Micromachines · 2025Article
- Advances and Opportunities of Mobile Health in the Postpandemic Era: Smartphonization of Wearable Devices and Wearable Deviceization of Smartphones.JMIR mHealth and uHealth · 2024Article
- Integration of force and IMU sensors for developing low-cost portable gait measurement system in lower extremities.Scientific reports · 2023Article
- Gait analysis using digital biomarkers including smart shoes in lumbar spinal canal stenosis: a scoping review.Frontiers in medicine · 2023Article
- Correlation between clinical scoring systems and quantitative MRI parameters in degenerative lumbar spinal stenosis.Journal of clinical orthopaedics and trauma · 2022Article
- State of the Art in Smart Portable, Wearable, Ingestible and Implantable Devices for Health Status Monitoring and Disease Management.Sensors (Basel, Switzerland) · 2022Review
- Estimating Ground Reaction Force and Center of Pressure Using Low-Cost Wearable Devices.IEEE transactions on bio-medical engineering · 2022Article
- Wearable Walking Assistant for Freezing of Gait With Environmental IoT Monitoring: A Contribution to the Discussion.Frontiers in public health · 2022Review
- Wearable Biosensors: An Alternative and Practical Approach in Healthcare and Disease Monitoring.Molecules (Basel, Switzerland) · 2021Review
- A Review of Smart Technologies Embedded in Shoes.Journal of medical systems · 2020Review
- Evolution of Wearable Devices with Real-Time Disease Monitoring for Personalized Healthcare.Nanomaterials (Basel, Switzerland) · 2019Review
- Wearables in Medicine.Advanced materials (Deerfield Beach, Fla.) · 2018Article
- Only walking matters-assessment following lumbar stenosis decompression.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 3 institutions in 1 country.
Funding
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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.