A vision for the future of wearable sensors in spine care and its challenges: narrative review

Lumbo-Pelvic Rhythm Monitoring Using Wearable Technology with Sensory Biofeedback: A Systematic Review

As an essential lower-back movement pattern, lumbo-pelvic rhythm (LPR) during forward trunk flexion and backward return has been investigated on a large scale. It has been suggested that abnormalities in lumbo-pelvic coordination are related to the risk of developing low back disorders. However, considerable differences in the approaches used to monitor LPR make it challenging to integrate findings from those investigations for future research. Therefore, the aim of this systematic review was to summarize the use of wearable technology for kinematic measurement with sensory biofeedback for LPR monitoring by assessing these technologies' specific capabilities and biofeedback capacities and exploring their practical viability based on sensor outcomes. The review was developed following the PRISMA guidelines, and the risk of bias was analyzed using the PREDro and STROBE scales. PubMed, Web of Science, Scopus, and IEEEXPLORE databases were searched for relevant studies, initially returning a total of 528 articles. Finally, we included eight articles featuring wearable devices with audio or vibration biofeedback. Differences in protocols and limitations were also observed. This novel study presents a review of wearable tracking devices for LPR motion-mediated biofeedback for the purpose of correcting lower back posture. More research is needed to determine the long-term effectiveness of these devices, as well as their most appropriate corresponding methodologies.

Physical Therapists' Acceptance of a Wearable, Fabric-Based Sensor System (Motion Tape) for Use in Clinical Practice: Qualitative Focus Group Study

BACKGROUND

Low back pain (LBP) is a costly global health condition that affects individuals of all ages and genders. Physical therapy (PT) is a commonly used and effective intervention for the management of LBP and incorporates movement assessment and therapeutic exercise. A newly developed wearable, fabric-based sensor system, Motion Tape, uses novel sensing and data modeling to measure lumbar spine movements unobtrusively and thus offers potential benefits when used in conjunction with PT. However, physical therapists' acceptance of Motion Tape remains unexplored.

OBJECTIVE

The primary aim of this research study was to evaluate physical therapists' acceptance of Motion Tape to be used for the management of LBP. The secondary aim was to explore physical therapists' recommendations for future device development.

METHODS

Licensed physical therapists from the American Physical Therapy Association Academy of Leadership Technology Special Interest Group participated in this study. Overall, 2 focus groups (FGs; N=8) were conducted, in which participants were presented with Motion Tape samples and examples of app data output on a poster. Informed by the Technology Acceptance Model, we conducted semistructured FGs and explored the wearability, usefulness, and ease of use of and suggestions for improvements in Motion Tape for PT management of LBP. FG data were transcribed and analyzed using rapid qualitative analysis.

RESULTS

Regarding wearability, participants perceived that Motion Tape would be able to adhere for several days, with some variability owing to external factors. Feedback was positive for the low-profile and universal fit, but discomfort owing to wires and potential friction with clothing was of concern. Other concerns included difficulty with self-application and potential skin sensitivity. Regarding usefulness, participants expressed that Motion Tape would enhance the efficiency and specificity of assessments and treatment. Regarding ease of use, participants stated that the app would be easy, but data management and challenges with interpretation were of concern. Physical therapists provided several recommendations for future design improvements including having a wireless system or removable wires, customizable sizes for the tape, and output including range of motion data and summary graphs and adding app features that consider patient input and context.

CONCLUSIONS

Several themes related to Motion Tape's wearability, usefulness, and ease of use were identified. Overall, physical therapists expressed acceptance of Motion Tape's potential for assessing and monitoring low back posture and movement, both within and outside clinical settings. Participants expressed that Motion Tape would be a valuable tool for the personalized treatment of LBP but highlighted several future improvements needed for Motion Tape to be used in practice.

Identifying Clinical Phenotypes in People Who Are Hispanic/Latino With Chronic Low Back Pain: Use of Sensor-Based Measures of Posture and Movement, Pain, and Psychological Factors

OBJECTIVE

The aim of this study was to identify clinical phenotypes using sensor-based measures of posture and movement, pain behavior, and psychological factors in Hispanic/Latino people with chronic low back pain (CLBP).

METHODS

Baseline measures from an ongoing clinical trial were analyzed for 81 Hispanic/Latino people with CLBP. Low back posture and movement were measured using commercial sensors during in-person testing and 8 hours of ecological monitoring. Magnitude, frequency, and duration of lumbar movements, sitting and standing postures were measured. Movement-evoked pain was assessed during in-person movement testing. Psychological measures included the Pain Catastrophizing Scale and the Fear Avoidance Beliefs Questionnaire. Random forest analysis was conducted to generate 2 groups and identify important variables that distinguish groups. Group differences in demographics, pain, psychological, and posture and movement variables were examined using t-tests and chi-square analyses.

RESULTS

Two subgroups of Hispanic/Latino people with CLBP were identified with minimal error (7.4% misclassification ["out-of-bag" error]). Ecological posture and movement measures best distinguished groups, although most movement-evoked pain and psychological measures did not. Group 1 had greater height and weight, lower movement frequency, more time in sitting, and less time in standing. Group 2 had a greater proportion of women than men, longer low back pain duration, higher movement frequency, more time in standing, and less time in sitting.

CONCLUSION

Two distinct clinical phenotypes of Hispanic/Latino people with CLBP were identified. One group was distinguished by greater height and weight and more sedentary posture and movement behavior; the second group had more women, longer duration of low back pain, higher lumbar spine movement frequency, and longer duration of standing postures.

IMPACT

Ecological measures of posture and movement are important for identifying 2 clinical phenotypes in Hispanic/Latino people with CLBP and may provide a basis for a more personalized plan of care.

LAY SUMMARY

Wearable sensors were used to measure low back posture and movement in Hispanic/Latino people with chronic low back pain. These posture and movement measures helped to identify 2 different clinical subgroups that will give physical therapists more information to better personalize treatment for chronic low back pain in Hispanic/Latino patients.

Concurrent Validity of the Ergotex Device for Measuring Low Back Posture

Highlighting the crucial role of monitoring and quantifying lumbopelvic rhythm for spinal curvature, the Ergotex IMU, a portable, lightweight, cost-effective, and energy-efficient technology, has been specifically designed for the pelvic and lumbar area. This study investigates the concurrent validity of the Ergotex device in measuring sagittal pelvic tilt angle. We utilized an observational, repeated measures design with healthy adult males (mean age: 39.3 ± 7.6 y, body mass: 82.2 ± 13.0 kg, body height: 179 ± 8 cm), comparing Ergotex with a 3D optical tracking system. Participants performed pelvic tilt movements in anterior, neutral, and posterior conditions. Statistical analysis included paired samples t-tests, Bland-Altman plots, and regression analysis. The findings show minimal systematic error (0.08° overall) and high agreement between the Ergotex and optical tracking, with most data points falling within limits of agreement of Bland-Altman plots (around ±2°). Significant differences were observed only in the anterior condition (0.35°, p < 0.05), with trivial effect sizes (ES = 0.08), indicating that these differences may not be clinically meaningful. The high Pearson's correlation coefficients across conditions underscore a robust linear relationship between devices (r > 0.9 for all conditions). Regression analysis showed a standard error of estimate (SEE) of 1.1° with small effect (standardized SEE < 0.26 for all conditions), meaning that the expected average deviation from the true value is around 1°. These findings validate the Ergotex as an effective, portable, and cost-efficient tool for assessing sagittal pelvic tilt, with practical implications in clinical and sports settings where traditional methods might be impractical or costly.

Digital Biomarkers and the Evolution of Spine Care Outcomes Measures: Smartphones and Wearables

Over the past generation, outcome measures in spine care have evolved from a reliance on clinician-reported assessment toward recognizing the importance of the patient's perspective and the wide incorporation of patient-reported outcomes (PROs). While patient-reported outcomes are now considered an integral component of outcomes assessments, they cannot wholly capture the state of a patient's functionality. There is a clear need for quantitative and objective patient-centered outcome measures. The pervasiveness of smartphones and wearable devices in modern society, which passively collect data related to health, has ushered in a new era of spine care outcome measurement. The patterns emerging from these data, so-called "digital biomarkers," can accurately describe characteristics of a patient's health, disease, or recovery state. Broadly, the spine care community has thus far concentrated on digital biomarkers related to mobility, although the researcher's toolkit is anticipated to expand in concert with advancements in technology. In this review of the nascent literature, we describe the evolution of spine care outcome measurements, outline how digital biomarkers can supplement current clinician-driven and patient-driven measures, appraise the present and future of the field in the modern era, as well as discuss present limitations and areas for further study, with a focus on smartphones (see Supplemental Digital Content , http://links.lww.com/NEU/D809 , for a similar appraisal of wearable devices).

Spine patient care with wearable medical technology: state-of-the-art, opportunities, and challenges: a systematic review

BACKGROUND CONTEXT

Healthcare reforms that demand quantitative outcomes and technical innovations have emphasized the use of Disability and Functional Outcome Measurements (DFOMs) to spinal conditions and interventions. Virtual healthcare has become increasingly important following the COVID-19 pandemic and wearable medical devices have proven to be a useful adjunct. Thus, given the advancement of wearable technology, broad adoption of commercial devices (ie, smartwatches, phone applications, and wearable monitors) by the general public, and the growing demand from consumers to take control of their health, the medical industry is now primed to formally incorporate evidence-based wearable device-mediated telehealth into standards of care.

PURPOSE

To (1) identify all wearable devices in the peer-reviewed literature that were used to assess DFOMs in Spine, (2) analyze clinical studies implementing such devices in spine care, and (3) provide clinical commentary on how such devices might be integrated into standards of care.

STUDY DESIGN/SETTING

A systematic review.

METHODS

A comprehensive systematic review was conducted in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Guidelines (PRISMA) across the following databases: PubMed; MEDLINE; EMBASE (Elsevier); and Scopus. Articles related to wearables systems in spine healthcare were selected. Extracted data was collected as per a predetermined checklist including wearable device type, study design, and clinical indices studied.

RESULTS

Of the 2,646 publications that were initially screened, 55 were extensively analyzed and selected for retrieval. Ultimately 39 publications were identified as being suitable for inclusion based on the relevance of their content to the core objectives of this systematic review. The most relevant studies were included, with a focus on wearables technologies that can be used in patients' home environments.

CONCLUSIONS

Wearable technologies mentioned in this paper have the potential to revolutionize spine healthcare through their ability to collect data continuously and in any environment. In this paper, the vast majority of wearable spine devices rely exclusively on accelerometers. Thus, these metrics provide information about general health rather than specific impairments caused by spinal conditions. As wearable technology becomes more prevalent in orthopedics, healthcare costs may be reduced and patient outcomes will improve. A combination of DFOMs gathered using a wearable device in conjunction with patient-reported outcomes and radiographic measurements will provide a comprehensive evaluation of a spine patient's health and assist the physician with patient-specific treatment decision-making. Establishing these ubiquitous diagnostic capabilities will allow improvement in patient monitoring and help us learn about postoperative recovery and the impact of our interventions.

Revolutionizing Spinal Care: Current Applications and Future Directions of Artificial Intelligence and Machine Learning

Artificial intelligence (AI) and machine learning (ML) are rapidly becoming integral components of modern healthcare, offering new avenues for diagnosis, treatment, and outcome prediction. This review explores their current applications and potential future in the field of spinal care. From enhancing imaging techniques to predicting patient outcomes, AI and ML are revolutionizing the way we approach spinal diseases. AI and ML have significantly improved spinal imaging by augmenting detection and classification capabilities, thereby boosting diagnostic accuracy. Predictive models have also been developed to guide treatment plans and foresee patient outcomes, driving a shift towards more personalized care. Looking towards the future, we envision AI and ML further ingraining themselves in spinal care with the development of algorithms capable of deciphering complex spinal pathologies to aid decision making. Despite the promise these technologies hold, their integration into clinical practice is not without challenges. Data quality, integration hurdles, data security, and ethical considerations are some of the key areas that need to be addressed for their successful and responsible implementation. In conclusion, AI and ML represent potent tools for transforming spinal care. Thoughtful and balanced integration of these technologies, guided by ethical considerations, can lead to significant advancements, ushering in an era of more personalized, effective, and efficient healthcare.

Between-day reliability of trunk orientation measured with smartphone sensors during sit-to-stand in asymptomatic individuals

BACKGROUND

Trunk kinematics during sit-to-stand is often impaired in individuals with musculoskeletal disorders. Trunk kinematics is commonly assessed in laboratories using motion capture; however, this equipment is often not available outside research centers. Smartphones are widely available and may be a suitable alternative to assess trunk orientation during sit-to-stand remotely.

OBJECTIVES

We investigated whether trunk orientation in the sagittal plane during sit-to-stand can be measured reliably between days when collected remotely using smartphones.

DESIGN

Cross-sectional study.

METHOD

Forty-three asymptomatic participants performed 15 sit-to-stand movements in two separate sessions remotely over videoconferencing. Trunk orientation was measured using each participant's smartphone. Absolute peak trunk orientation in the sagittal plane was extracted during standing, sitting, stand up and sit down. Relative trunk orientation was calculated as the difference between sitting and stand up, or sitting and sit down. Reliability was assessed using Intraclass Correlation Coefficient (ICC_2,k), Standard Error of Measurement (SEM) and Minimal Detectable change (MDC). Between day bias and between-gender differences were assessed using T tests.

RESULTS

All measures showed good reliability (ICC_2,k > 0.80; SEM < 5.6°; MDC < 13.6°) and no between-day bias (p > 0.31). Relative measures were more consistent (ICC_2,k > 0.88; SEM < 3.6°; MDC < 9.9°). No between-gender differences were observed for relative orientation (p > 0.75).

CONCLUSIONS

Sagittal trunk orientation during sitting, standing, and sit-to-stand can be measured reliably when asymptomatic individuals use their own smartphones supervised over videoconferencing. These findings support the use of smartphone sensors for assessing how trunk orientation changes over time, which may assist physiotherapists assess movement patterns of individuals with musculoskeletal disorders remotely.