Measurement of the Human Balance with one Inertial Sensor in Lower Back

Abstract Instantaneous crank power does not equal total joint power if a rider's centre of mass (CoM) gains and loses mechanical energy. Thus, estimating CoM motion and the associated energy changes can provide valuable information about cycling performance. To date, an accurate and precise method for tracking CoM motion during outdoor cycling has not been validated. Purpose: To assess the suitability of an inertial measurement unit (IMU) for tracking CoM motion during non-seated cycling by comparing vertical displacement derived from an inertial sensor mounted to the lower back of the rider to an attached marker cluster and to a kinematic estimate of vertical CoM displacement from a full-body musculoskeletal model (Model). Methods: IMU and motion capture data were collected synchronously for 10 seconds while participants (n = 7) cycled on an ergometer in a non-seated posture at three power outputs and two cadences. A limits of agreement analysis, corrected for repeated measures, was performed on the range of vertical displacement between the IMU and the two other measures. A total of 303 crank cycles were analysed. Results: The IMU measured vertical displacement of the marker cluster with high accuracy (1.6 mm) and precision (3.5 mm) but substantially overestimated the kinematic estimate of rider CoM displacement. Conclusion: We interpret these findings as evidence that a single IMU placed on the lower back is unsuitable for tracking rider CoM displacement during non-seated cycling if the linearly increasing overestimation is unaccounted for.

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Transportation period detection for physical activity monitoring using an inertial sensor on the lower-back

10.1183/13993003.congress-2016.pa2049 ◽

2016 ◽

Author(s):

Aki Kunikoshi ◽

Martijn Niessen ◽

Evert Pengel ◽

Bas Huijben ◽

Rob C. van Lummel

Keyword(s):

Physical Activity ◽

Inertial Sensor ◽

Activity Monitoring ◽

Physical Activity Monitoring ◽

Lower Back ◽

Period Detection

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Functional Evaluation Using Inertial Measurement of Back School Therapy in Lower Back Pain

Sensors ◽

10.3390/s20020531 ◽

2020 ◽

Vol 20 (2) ◽

pp. 531

Author(s):

Claudia Celletti ◽

Roberta Mollica ◽

Cristina Ferrario ◽

Manuela Galli ◽

Filippo Camerota

Keyword(s):

Back Pain ◽

Lower Back Pain ◽

Inertial Sensor ◽

Functional Improvement ◽

Functional Evaluation ◽

Timed Up And Go ◽

Back School ◽

Lower Back ◽

Before And After ◽

Reduction Of Pain

Lower back pain is an extremely common health problem and globally causes more disability than any other condition. Among other rehabilitation approaches, back schools are interventions comprising both an educational component and exercises. Normally, the main outcome evaluated is pain reduction. The aim of this study was to evaluate not only the efficacy of back school therapy in reducing pain, but also the functional improvement. Patients with lower back pain were clinically and functionally evaluated; in particular, the timed “up and go” test with inertial movement sensor was studied before and after back school therapy. Forty-four patients completed the program, and the results showed not only a reduction of pain, but also an improvement in several parameters of the timed up and go test, especially in temporal parameters (namely duration and velocity). The application of the inertial sensor measurement in evaluating functional aspects seems to be useful and promising in assessing the aspects that are not strictly correlated to the specific pathology, as well as in rehabilitation management.

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Algorithms for Walking Speed Estimation Using a Lower-Back-Worn Inertial Sensor: A Cross-Validation on Speed Ranges

IEEE Transactions on Neural Systems and Rehabilitation Engineering ◽

10.1109/tnsre.2021.3111681 ◽

2021 ◽

Vol 29 ◽

pp. 1955-1964

Author(s):

A. Soltani ◽

K. Aminian ◽

C. Mazza ◽

A. Cereatti ◽

L. Palmerini ◽

...

Keyword(s):

Cross Validation ◽

Walking Speed ◽

Inertial Sensor ◽

Speed Estimation ◽

Lower Back

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Template-Based Recognition of Human Locomotion in IMU Sensor Data Using Dynamic Time Warping

Sensors ◽

10.3390/s21082601 ◽

2021 ◽

Vol 21 (8) ◽

pp. 2601

Author(s):

Kim S. Sczuka ◽

Marc Schneider ◽

Alan K. Bourke ◽

Sabato Mellone ◽

Ngaire Kerse ◽

...

Keyword(s):

Dynamic Time Warping ◽

Inertial Sensor ◽

Vigorous Physical Activity ◽

Human Locomotion ◽

Recognition Algorithm ◽

Stair Climbing ◽

Sensor Data ◽

Time Warping ◽

Lower Back ◽

Dynamic Time

Increased levels of light, moderate and vigorous physical activity (PA) are positively associated with health benefits. Therefore, sensor-based human activity recognition can identify different types and levels of PA. In this paper, we propose a two-layer locomotion recognition method using dynamic time warping applied to inertial sensor data. Based on a video-validated dataset (ADAPT), which included inertial sensor data recorded at the lower back (L5 position) during an unsupervised task-based free-living protocol, the recognition algorithm was developed, validated and tested. As a first step, we focused on the identification of locomotion activities walking, ascending and descending stairs. These activities are difficult to differentiate due to a high similarity. The results showed that walking could be recognized with a sensitivity of 88% and a specificity of 89%. Specificity for stair climbing was higher compared to walking, but sensitivity was noticeably decreased. In most cases of misclassification, stair climbing was falsely detected as walking, with only 0.2–5% not assigned to any of the chosen types of locomotion. Our results demonstrate a promising approach to recognize and differentiate human locomotion within a variety of daily activities.

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A method for tracking centre of mass displacement during non-seated cycling using an inertial sensor

10.31236/osf.io/htr4k ◽

2020 ◽

Author(s):

Ross D. Wilkinson ◽

Glen A. Lichtwark

Keyword(s):

Repeated Measures ◽

Inertial Sensor ◽

Mechanical Energy ◽

Vertical Displacement ◽

Cycling Performance ◽

Measurement Unit ◽

Centre Of Mass ◽

Joint Power ◽

Lower Back ◽

Marker Cluster

Instantaneous crank power does not equal total joint power if a rider's centre of mass (CoM) gains and loses mechanical energy. Thus, estimating CoM motion and the associated energy changes can provide valuable information about cycling performance. To date, an accurate and precise method for tracking CoM motion during outdoor cycling has not been validated. \textbf{Purpose:} To assess the suitability of an inertial measurement unit (IMU) for tracking CoM motion during non-seated cycling by comparing vertical displacement derived from an inertial sensor mounted to the lower back of the rider to an attached marker cluster and to a kinematic estimate of vertical CoM displacement from a full-body musculoskeletal model (Model). \textbf{Methods:} IMU and motion capture data were collected synchronously for 10 seconds while participants ($n=7$) cycled on an ergometer in a non-seated posture at three power outputs and two cadences. A limits of agreement analysis, corrected for repeated measures, was performed on the range of vertical displacement between the IMU and the two other measures. A total of 303 crank cycles were analysed. \textbf{Results:} The IMU measured vertical displacement of the marker cluster with high accuracy (1.6 mm) and precision (3.5 mm) but substantially overestimated the kinematic estimate of rider CoM displacement. \textbf{Conclusion:} We interpret these findings as evidence that a single IMU placed on the lower back is unsuitable for tracking rider CoM displacement during non-seated cycling if the linearly increasing overestimation is unaccounted for.

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Measurement of Pelvic Orientation Angles during Sprinting Using a Single Inertial Sensor

Proceedings ◽

10.3390/proceedings2020049010 ◽

2020 ◽

Vol 49 (1) ◽

pp. 10 ◽

Cited By ~ 2

Author(s):

Tomohito Wada ◽

Ryu Nagahara ◽

Sam Gleadhill ◽

Tatsuro Ishizuka ◽

Hayato Ohnuma ◽

...

Keyword(s):

Motion Capture ◽

Mean Squared Error ◽

Inertial Sensor ◽

Three Dimensional ◽

Motion Capture System ◽

Fusion Algorithm ◽

Lower Back ◽

Sensor Orientation ◽

Optical Motion ◽

Optical Motion Capture

The purpose of this study was to elucidate pelvic orientation angles using a single lower back-mounted inertial sensor during sprinting. A single inertial sensor was attached to each sprinter’s lower back, used to measure continuous pelvic movements including pelvic obliquity (roll), anterior-posterior tilt (pitch) and rotation (yaw) during sprinting from a straight to bend section. The pelvic orientation angles were estimated with the three-dimensional sensor orientation using a sensor fusion algorithm. Absolute angles derived from the sensor were compared with angles obtained from an optical motion capture system over a 15 m length. The root mean squared error between the sensor and motion capture data were 4.1° for roll, 2.8° for pitch and 3.6° for yaw. Therefore, the sensor was comparable to the motion capture system for tracking pelvic angle changes. The inertial sensor is now supported as a valid tool to measure movements of the pelvis during sprinting.

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Machine learning-based distinction of left and right foot contacts in lower back inertial sensor gait data

10.1109/embc46164.2021.9630653 ◽

2021 ◽

Author(s):

Martin Ullrich ◽

Arne Kuderle ◽

Luca Reggi ◽

Andrea Cereatti ◽

Bjoern M. Eskofier ◽

...

Keyword(s):

Machine Learning ◽

Inertial Sensor ◽

Lower Back ◽

Left And Right

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