Inertial measurement units: A brief state of the art on gait analysis

Ribeiro, Nuno Ferrete; Santos, Cristina P.

doi:10.1109/enbeng.2017.7889458

Cited by 20 publications

(3 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Listing a full range of IMU devices and their applications is outside of the scope of this narrative review. However, extensive reviews of commercially available IMUs and their respective applications can be found elsewhere, e.g., [26,35,60,61].…”

Section: Inertial Measurement Unitsmentioning

confidence: 99%

IoT-Enabled Gait Assessment: The Next Step for Habitual Monitoring

Young

Mason

Morris

et al. 2023

Sensors

View full text Add to dashboard Cite

Walking/gait quality is a useful clinical tool to assess general health and is now broadly described as the sixth vital sign. This has been mediated by advances in sensing technology, including instrumented walkways and three-dimensional motion capture. However, it is wearable technology innovation that has spawned the highest growth in instrumented gait assessment due to the capabilities for monitoring within and beyond the laboratory. Specifically, instrumented gait assessment with wearable inertial measurement units (IMUs) has provided more readily deployable devices for use in any environment. Contemporary IMU-based gait assessment research has shown evidence of the robust quantifying of important clinical gait outcomes in, e.g., neurological disorders to gather more insightful habitual data in the home and community, given the relatively low cost and portability of IMUs. The aim of this narrative review is to describe the ongoing research regarding the need to move gait assessment out of bespoke settings into habitual environments and to consider the shortcomings and inefficiencies that are common within the field. Accordingly, we broadly explore how the Internet of Things (IoT) could better enable routine gait assessment beyond bespoke settings. As IMU-based wearables and algorithms mature in their corroboration with alternate technologies, such as computer vision, edge computing, and pose estimation, the role of IoT communication will enable new opportunities for remote gait assessment.

show abstract

Section: Inertial Measurement Unitsmentioning

confidence: 99%

IoT-Enabled Gait Assessment: The Next Step for Habitual Monitoring

Young

Mason

Morris

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…IMU-based systems offered advantages such as being lightweight, cost-effective, and portable. However, there were certain concerns related to angle calculation that needs careful consideration [287]. Therefore, selecting the appropriate motion tracking system became crucial and depended on the specific use-case at hand.…”

Section: Summary Of Evidencementioning

confidence: 99%

Upper extremity asymmetry due to nerve injuries or central neurologic conditions: a scoping review

Bhat,

Shin,

Kaufman

2023

J NeuroEngineering Rehabil

View full text Add to dashboard Cite

Background Peripheral nerve injuries and central neurologic conditions can result in extensive disabilities. In cases with unilateral impairment, assessing the asymmetry between the upper extremity has been used to assess outcomes of treatment and severity of injury. A wide variety of validated and novel tests and sensors have been utilized to determine the upper extremity asymmetry. The purpose of this article is to review the literature and define the current state of the art for describing upper extremity asymmetry in patients with peripheral nerve injuries or central neurologic conditions. Method An electronic literature search of PubMed, Scopus, Web of Science, OVID was performed for publications between 2000 to 2022. Eligibility criteria were subjects with neurological conditions/injuries who were analyzed for dissimilarities in use between the upper extremities. Data related to study population, target condition/injury, types of tests performed, sensors used, real-world data collection, outcome measures of interest, and results of the study were extracted. Sackett’s Level of Evidence was used to judge the quality of the articles. Results Of the 7281 unique articles, 112 articles met the inclusion criteria for the review. Eight target conditions/injuries were identified (Brachial Plexus Injury, Cerebral Palsy, Multiple Sclerosis, Parkinson’s Disease, Peripheral Nerve Injury, Spinal Cord Injury, Schizophrenia, and stroke). The tests performed were classified into thirteen categories based on the nature of the test and data collected. The general results related to upper extremity asymmetry were listed for all the reviewed articles. Stroke was the most studied condition, followed by cerebral palsy, with kinematics and strength measurement tests being the most frequently used tests. Studies with a level of evidence level II and III increased between 2000 and 2021. The use of real-world evidence-based data, and objective data collection tests also increased in the same period. Conclusion Adequately powered randomized controlled trials should be used to study upper extremity asymmetry. Neurological conditions other than stroke should be studied further. Upper extremity asymmetry should be measured using objective outcome measures like motion tracking and activity monitoring in the patient’s daily living environment.

show abstract

“…Changes in human gait can be monitored through a variety of parameters including walking speed [2, 3], step length [4, 5], or cadence [6]. Besides the analysis of human gait in special gait laboratories, inertial measurement units can be used to monitor gait in free-living, real-world environments [7]. Small body-mounted sensors represent a promising alternative to specialized gait analysis facilities, enabling unobtrusive long-term monitoring in the subject’s habitual environment.…”

Section: Introductionmentioning

confidence: 99%

Robust Step Detection from Different Waist-Worn Sensor Positions: Implications for Clinical Studies

et al. 2020

View full text Add to dashboard Cite

Analyzing human gait with inertial sensors provides valuable insights into a wide range of health impairments, including many musculoskeletal and neurological diseases. A representative and reliable assessment of gait requires continuous monitoring over long periods and ideally takes place in the subjects’ habitual environment (real-world). An inconsistent sensor wearing position can affect gait characterization and influence clinical study results, thus clinical study protocols are typically highly proscriptive, instructing all participants to wear the sensor in a uniform manner. This restrictive approach improves data quality but reduces overall adherence. In this work, we analyze the impact of altering the sensor wearing position around the waist on sensor signal and step detection. We demonstrate that an asymmetrically worn sensor leads to additional odd-harmonic frequency components in the frequency spectrum. We propose a robust solution for step detection based on autocorrelation to overcome sensor position variation (sensitivity = 0.99, precision = 0.99). The proposed solution reduces the impact of inconsistent sensor positioning on gait characterization in clinical studies, thus providing more flexibility to protocol implementation and more freedom to participants to wear the sensor in the position most comfortable to them. This work is a first step towards truly position-agnostic gait assessment in clinical settings.

show abstract

Inertial measurement units: A brief state of the art on gait analysis

Cited by 20 publications

References 24 publications

IoT-Enabled Gait Assessment: The Next Step for Habitual Monitoring

IoT-Enabled Gait Assessment: The Next Step for Habitual Monitoring

Upper extremity asymmetry due to nerve injuries or central neurologic conditions: a scoping review

Robust Step Detection from Different Waist-Worn Sensor Positions: Implications for Clinical Studies

Contact Info

Product

Resources

About