A portable inertial sensing-based spinal motion measurement system for low back pain assessment

Can subjective pain be inferred from objective physiological data? Evidence from patients with sickle cell disease

Patients with sickle cell disease (SCD) experience lifelong struggles with both chronic and acute pain, often requiring medical interventMaion. Pain can be managed with medications, but dosages must balance the goal of pain mitigation against the risks of tolerance, addiction and other adverse effects. Setting appropriate dosages requires knowledge of a patient’s subjective pain, but collecting pain reports from patients can be difficult for clinicians and disruptive for patients, and is only possible when patients are awake and communicative. Here we investigate methods for estimating SCD patients’ pain levels indirectly using vital signs that are routinely collected and documented in medical records. Using machine learning, we develop both sequential and non-sequential probabilistic models that can be used to infer pain levels or changes in pain from sequences of these physiological measures. We demonstrate that these models outperform null models and that objective physiological data can be used to inform estimates for subjective pain.

Understanding subjective human pain remains a major challenge. If objective data could be used in place of reported pain levels, it could reduce patient burdens and enable the collection of much larger data sets that could deepen our understanding of causes of pain and allow for accurate forecasting and more effective pain management. Here we apply two machine learning approaches to data from patients with sickle cell disease, who often experience debilitating pain crises. Using vital sign data routinely collected in hospital settings including respiratory rate, heart rate, and blood pressure and amidst the real-world challenges of irregular timing, missing data, and inter-patient variation, we demonstrate that these models outperform baseline models in estimating subjective pain, distinguishing between typical and atypical pain levels, and detecting changes in pain. Once trained, these types of models could be used to improve pain estimates in real time in the absence of direct pain reports.

A novel IMU-based clinical assessment protocol for Axial Spondyloarthritis: a protocol validation study

Clinical assessment of spinal impairment in Axial Spondyloarthritis is currently performed using the Bath Ankylosing Spondylitis Metrological Index (BASMI). Despite being appreciated for its simplicity, the BASMI index lacks sensitivity and specificity of spinal changes, demonstrating poor association with radiographical range of motion (ROM). Inertial measurement units (IMUs) have shown promising results as a cost-effective method to quantitatively examine movement of the human body, however errors due to sensor angular drift have limited their application to a clinical space. Therefore, this article presents a wearable sensor protocol that facilitates unrestrained orientation measurements in space while limiting sensor angular drift through a novel constraint-based approach. Eleven healthy male participants performed five BASMI-inspired functional movements where spinal ROM and continuous kinematics were calculated for five spine segments and four spinal joint levels (lumbar, lower thoracic, upper thoracic and cervical). A Bland-Altman analysis was used to assess the level of agreement on range of motion measurements, whilst intraclass correlation coefficient (ICC), standardised error measurement, and minimum detectable change (MDC) to assess relative and absolute reliability. Continuous kinematics error was investigated through root mean square error (RMSE), maximum absolute error (MAE) and Spearman correlation coefficient (ρ). The overall error in the measurement of continuous kinematic measures was low in both the sagittal (RMSE = 2.1°), and frontal plane (RMSE = 2.3°). ROM limits of agreement (LoA) and minimum detectable change were excellent for the sagittal plane (maximum value LoA 1.9° and MDC 2.4°) and fair for lateral flexion (overall value LoA 4.8° and MDC 5.7°). The reliability analysis showed excellent level of agreement (ICC > 0.9) for both segment and joint ROM across all movements. The results from this study demonstrated better or equivalent accuracy than previous studies and were considered acceptable for application in a clinical setting. The protocol has shown to be a valuable tool for the assessment of spinal ROM and kinematics, but a clinical validation study on Axial Spondyloarthritis patients is required for the development and testing of a novel mobility index.

Differences in movement limitations in different low back pain severity in functional tests using an RGB-D camera

Low back pain (LBP) can lead to motor control disturbance which can be one of the causes of reoccurrence of the complaint. It is important to improve our knowledge of movement related disturbances during assessment in LBP and to classify patients according to the severity. The aim of this study is to present differences in kinematic variables using a RGB-D camera in order to classify LBP patients with different severity. A cross-sectional study was carried out. Subjects with non-specific subacute and chronic LBP were screened 6 weeks following an episode. Functional tests were bending trunk test, sock test and sit to stand test. Participants performed as many repetitions as possible during 30 s for each functional test. Angular displacement, velocity and acceleration, linear acceleration, time and repetitions were analysed. Participants were divided into two groups to determine their different LBP severity with a k-means clusters according to the results obtained in Roland Morris questionnaire (RMQ). Comparing different severity groups based on RMQ score (high impact = 17.15, low impact = 7.47), bending trunk test obtained significative differences in linear acceleration (p = 0.002-0.01). The differences of total linear acceleration during the Sit to Stand test were significative (p = 0.004-0.02). Sock test showed not significative differences between groups (p > 0.05). Linear acceleration variables during Sit to Stand test and Bending trunk test were significatively different between the different severity groups. RGB-D camera system and functional tests can detect kinematic differences in different type of LBP according to the functionality. Trial registration: ClinicalTrials.gov NCT03293095 "Functional Task Kinematic in Musculoskeletal Pathology" September 26, 2017.

Validation, Reliability, and Responsiveness Outcomes Of Kinematic Assessment With An RGB-D Camera To Analyze Movement In Subacute And Chronic Low Back Pain

Background: The RGB-D camera is an alternative to asses kinematics in order to obtain objective measurements of functional limitations. The aim of this study is to analyze the validity, reliability, and responsiveness of the motion capture depth camera in sub-acute and chronic low back pain patients. Methods: Thirty subjects (18–65 years) with non-specific lumbar pain were screened 6 weeks following an episode. RGB-D camera measurements were compared with an inertial measurement unit. Functional tests included climbing stairs, bending, reaching sock, lie-to-sit, sit-to-stand, and timed up-and-go. Subjects performed the maximum number of repetitions during 30 s. Validity was analyzed using Spearman’s correlation, reliability of repetitions was calculated by the intraclass correlation coefficient and the standard error of measurement, and receiver operating characteristic curves were calculated to assess the responsiveness. Results: The kinematic analysis obtained variable results according to the test. The time variable had good values in the validity and reliability of all tests (r = 0.93–1.00, (intraclass correlation coefficient (ICC) = 0.62–0.93). Regarding kinematics, the best results were obtained in bending test, sock test, and sit-to-stand test (r = 0.53–0.80, ICC = 0.64–0.83, area under the curve (AUC) = 0.55–84). Conclusion: Functional tasks, such as bending, sit-to-stand, reaching, and putting on sock, assessed with the RGB-D camera, revealed acceptable validity, reliability, and responsiveness in the assessment of patients with low back pain (LBP). Trial registration: ClinicalTrials.gov NCT03293095 “Functional Task Kinematic in Musculoskeletal Pathology” 26 September 2017

Is there evidence to use kinematic/kinetic measures clinically in low back pain patients? A systematic review

BACKGROUND

Currently, there is a widespread reliance on self-reported questionnaires to assess low back pain patients. However, it has been suggested that objective measures of low back pain patients' functional status should be used to aid clinical assessment. The aim of this study is to systematically review which kinematic /kinetic parameters have been used to assess low back pain patients against healthy controls and to propose clinical kinematic/kinetic measures.

METHODS

PubMed, Embase and Scopus databases were searched for relevant studies. Reference lists of selected studies and hand searches were performed. Studies had to compare people with and without non-specific low back pain while performing functional tasks and report body segment/joint kinematic and/or kinetic data. Two reviewers independently identified relevant papers.

FINDINGS

Sixty-two studies were included. Common biases identified were lack of assessor blinding and sample size calculation, use of samples of convenience, and poor experimental protocol standardization. Studies had small sample sizes. Range of motion maneuvers were the main task performed (33/62). Kinematic/kinetic data of different individual or combination of body segments/joints were reported among the studies, commonest was to assess the hip joint and lumbar segment motion (13/62). Only one study described full body movement. The most commonly reported outcome was range of motion. Statistically significant differences between controls and low back pain groups were reported for different outcomes among the studies. Moreover, when the same outcome was reported disagreements were noted.

INTERPRETATION

The literature to date offers limited and inconsistent evidence of kinematic/kinetic measures in low back pain patients that could be used clinically.

Wearable technology for spine movement assessment: A systematic review

Continuous monitoring of spine movement function could enhance our understanding of low back pain development. Wearable technologies have gained popularity as promising alternative to laboratory systems in allowing ambulatory movement analysis. This paper aims to review the state of art of current use of wearable technology to assess spine kinematics and kinetics. Four electronic databases and reference lists of relevant articles were searched to find studies employing wearable technologies to assess the spine in adults performing dynamic movements. Two reviewers independently identified relevant papers. Customised data extraction and quality appraisal form were developed to extrapolate key details and identify risk of biases of each study. Twenty-two articles were retrieved that met the inclusion criteria: 12 were deemed of medium quality (score 33.4-66.7%), and 10 of high quality (score >66.8%). The majority of articles (19/22) reported validation type studies. Only 6 reported data collection in real-life environments. Multiple sensors type were used: electrogoniometers (3/22), strain gauges based sensors (3/22), textile piezoresistive sensor (1/22) and accelerometers often used with gyroscopes and magnetometers (15/22). Two sensors units were mainly used and placing was commonly reported on the spine lumbar and sacral regions. The sensors were often wired to data transmitter/logger resulting in cumbersome systems. Outcomes were mostly reported relative to the lumbar segment and in the sagittal plane, including angles, range of motion, angular velocity, joint moments and forces. This review demonstrates the applicability of wearable technology to assess the spine, although this technique is still at an early stage of development.