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Biomechanical Analysis of Motion and Postural Control: Sensors Methods and Data Analytics

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".

Deadline for manuscript submissions: closed (31 May 2022) | Viewed by 28822

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Dr. Leandro José Rodrigues Machado

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Guest Editor

Department of Biomechanics, Faculty of Sport, University of Porto, 4200-450 Porto, Portugal
Interests: biomechanics; data analytics; gait analysis; swimming analysis; para-sports analysis
Special Issues, Collections and Topics in MDPI journals

Dr. Miguel Correia

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Guest Editor

Department of Electrical and Computer Engineering, Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal
Interests: sensors; wearables; medical devices; biomedical instrumentation; smart textiles; motion analysis; gait analysis; perception
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The aim of this Special Issue of the Sensors journal is to publish articles on the thematic of human motion, balance, and postural control. Articles covering a wide range of applications and situations where sensors can be employed are foreseen, whether on concrete sensor use or on treatment of sensor generated data, in the context of Biomechanics:

- From walking to running.

- From swimming to jumping.

- From day-to-day activities to sports motions.

- For people with and without impairments.

- From wearable sensors to external sensors.

- From local to global data integration and data analysis.

- From IMUs to EMG to ...

Articles found in this Special Issue may contribute to a better understanding of questions such as:

- How to warrant the correct positioning of wearable sensors? Should more than one sensor be used per body segment? Use complimentary types of sensors? Use larger sensors?

- How smart does a sensor need to be, or a local group of sensors?

- How to get submillimetre precision with markerless setups for 3D motion analysis? How many people can be followed simultaneously?

- How to get the system to evaluate in real life conditions, at home, at work, outdoors?

- Can wearable sensors systems help prevent falls or assist balance or gait?

- How to increase sensors systems reliability?

Dr. Leandro José Rodrigues Machado
Prof. Miguel Correia
Guest Editors

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Keywords

biomechanics
sports
day-to-day activities
impairments
data processing
wearable
markerless

Published Papers (11 papers)

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Research

10 pages, 2230 KiB

Open AccessArticle

A New Quantitative Gait Analysis Method Based on Oscillatory Mechanical Energies Measured near Body Center of Mass

by Derek Cheung, Jeff Cheung, Vicky Cheung and Li Jin

Sensors 2022, 22(22), 8656; https://doi.org/10.3390/s22228656 - 09 Nov 2022

Viewed by 1289

Abstract

Human locomotion involves the modulation of whole-body mechanical energy, which can be approximated by the motion dynamics at the body’s center of mass (BCOM). This study introduces a new method to measure gait efficiency based on BCOM oscillatory kinetic energy patterns using a single inertia measurement unit (IMU). Forty-seven participants completed an overground walk test at a self-selected speed. The average oscillatory energy (OE) at BCOM during walking was derived from measured acceleration data. The total OE showed a positive correlation with forward-walking velocity. The ratio of total OE to constant forward kinetic energy for healthy adults varied from ~1–5%, which can be considered the percent of oscillatory energy required to maintain gait posture for a given forward-walking velocity. Mathematically, this ratio is proportional to the square of the periodic peak-to-peak displacement of BCOM. Individuals with gait impairments exhibited a higher percentage of oscillatory energy, typically >6%. This wearable IMU-based method has the potential to be an effective tool for the rapid, quantitative assessment of gait efficiency in clinical and rehabilitation settings. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensors Methods and Data Analytics)

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22 pages, 16721 KiB

Open AccessArticle

Intelligent Posture Training: Machine-Learning-Powered Human Sitting Posture Recognition Based on a Pressure-Sensing IoT Cushion

by Katia Bourahmoune, Karlos Ishac and Toshiyuki Amagasa

Sensors 2022, 22(14), 5337; https://doi.org/10.3390/s22145337 - 17 Jul 2022

Cited by 14 | Viewed by 3908

Abstract

We present a solution for intelligent posture training based on accurate, real-time sitting posture monitoring using the LifeChair IoT cushion and supervised machine learning from pressure sensing and user body data. We demonstrate our system’s performance in sitting posture and seated stretch recognition tasks with over 98.82% accuracy in recognizing 15 different sitting postures and 97.94% in recognizing six seated stretches. We also show that user BMI divergence significantly affects posture recognition accuracy using machine learning. We validate our method’s performance in five different real-world workplace environments and discuss training strategies for the machine learning models. Finally, we propose the first smart posture data-driven stretch recommendation system in alignment with physiotherapy standards. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensors Methods and Data Analytics)

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14 pages, 649 KiB

Open AccessArticle

Balance and Posture in Children and Adolescents: A Cross-Sectional Study

by Nelson Azevedo, José Carlos Ribeiro and Leandro Machado

Sensors 2022, 22(13), 4973; https://doi.org/10.3390/s22134973 - 30 Jun 2022

Cited by 5 | Viewed by 2862

Abstract

Balance and posture are two topics that have been extensively studied, although with some conflicting findings. Therefore, the aim of this work is to analyze the relationship between the postural angles of the spine in the sagittal plane and the stable static balance. A cross-sectional study was conducted with children and adolescents from schools in northern Portugal in 2019. An online questionnaire was used to characterize the sample and analyze back pain. Spinal postural angle assessment (pelvic, lumbar, and thoracic) was performed using the Spinal Mouse^®, while stabilometry assessment was performed using Namrol^® Podoprint^®. Statistical significance was set as α = 0.05. The results showed that girls have better balance variables. There is a weak correlation between the anthropometric variables with stabilometry variables and the postural angles. This correlation is mostly negative, except for the thoracic spine with anthropometric variables and the lumbar spine with BMI. The results showed that postural angles of the spine are poor predictors of the stabilometric variables. Concerning back pain, increasing the postural angle of the thoracic spine increases the odds ratio of manifestation of back pain by 3%. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensors Methods and Data Analytics)

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12 pages, 16050 KiB

Open AccessArticle

Determination of the 3D Human Spine Posture from Wearable Inertial Sensors and a Multibody Model of the Spine

by Florian Michaud, Urbano Lugrís and Javier Cuadrado

Sensors 2022, 22(13), 4796; https://doi.org/10.3390/s22134796 - 24 Jun 2022

Cited by 7 | Viewed by 2767

Abstract

Determination of spine posture is of great interest for the effective prevention, evaluation, treatment and evolution monitoring of spinal disorders. Limitations of traditional imaging systems, including cost, radiation exposure (for X-ray based systems), projection volume issues and subject positioning requirements, etc., make non-invasive motion assessment tools effective alternatives for clinical and non-clinical use. In this work, a procedure was developed to obtain a subject-specific multibody model of the spine using either inertial or optical sensors and, based on this multibody model, to estimate the locations and orientations of the 17 vertebrae constituting the thoracolumbar spine. The number and calibration of the sensors, angular offsets, scaling difficulties and gender differences were addressed to achieve an accurate 3D-representation of the spine. The approach was validated by comparing the estimated positions of the sensors on 14 healthy subjects with those provided by an optical motion capture system. A mean position error of lower than 12 mm was obtained, thus showing that the proposed method can offer an effective non-invasive tool for the assessment of spine posture. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensors Methods and Data Analytics)

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17 pages, 4301 KiB

Open AccessArticle

Quantitative Gait Analysis of Patients with Severe Symptomatic Spinal Stenosis Utilizing the Gait Profile Score: An Observational Clinical Study

by Jan Lodin, Marek Jelínek, Martin Sameš and Petr Vachata

Sensors 2022, 22(4), 1633; https://doi.org/10.3390/s22041633 - 19 Feb 2022

Cited by 2 | Viewed by 2289

Abstract

Lumbar spine stenosis (LSS) typically manifests with neurogenic claudication, altering patients’ gait. The use of optoelectronic systems has allowed clinicians to perform 3D quantitative gait analysis to quantify and understand these alterations. Although several authors have presented analysis of spatiotemporal gait parameters, data concerning kinematic parameters is lacking. Fifteen patients with LSS were matched with 15 healthy controls. Quantitative gait analysis utilizing optoelectronic techniques was performed for each pair of subjects in a specialized laboratory. Statistical comparison of patients and controls was performed to determine differences in spatiotemporal parameters and the Gait Profile Score (GPS). Statistically significant differences were found between patient and control groups for all spatiotemporal parameters. Patients had significantly different overall GPS (p = 0.004) and had limited internal/external pelvic rotation (p < 0.001) and cranial/caudal movement (p = 0.034), limited hip extension (p = 0.012) and abduction/adduction (p = 0.012) and limited ankle plantar flexion (p < 0.001). In conclusion, patients with LSS have significantly altered gait patterns in three regions (pelvis, hip and ankle) compared to healthy controls. Analysis of kinematic graphs has given insight into gait pathophysiology of patients with LSS and the use of GPS will allow us to quantify surgical results in the future. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensors Methods and Data Analytics)

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12 pages, 1364 KiB

Open AccessArticle

Evaluation of Upper Limb Joint Contribution to Racket Head Speed in Elite Tennis Players Using IMU Sensors: Comparison between the Cross-Court and Inside-Out Attacking Forehand Drive

by Bruno Pedro, Filipa João, Jerusa P. R. Lara, Silvia Cabral, João Carvalho and António P. Veloso

Sensors 2022, 22(3), 1283; https://doi.org/10.3390/s22031283 - 08 Feb 2022

Cited by 9 | Viewed by 2870

Abstract

This study aimed to quantify and compare the upper limb angular kinematics and its contributions to the racket head speed between the cross-court (CC) and inside-out (IO) attacking tennis forehand of elite tennis players in a competitive environment. A new approach was used to study the forehand drive with mini-inertial sensors of motion capture to record the kinematic data. Six strokes in each direction per participant (72 shots in total) were chosen for analysis. Upper limb kinematics were calculated in the Visual 3D platform (Visual 3D Professional V5.01.21, C-motion, Germantown, MD, USA). The method used to calculate the upper limb’s contributions was performed with MATLAB software and used the segment’s (upper arm, forearm and hand) angular velocities and their respective displacement vectors obtained through the inertial sensors. Upper limb kinematics demonstrated a higher shoulder rotation in the IO direction with significant differences at the end of the backswing, which could be a key factor in distinguishing the two directions of the shot. Results also demonstrated that the horizontal flexion of the upper arm (around the shoulder joint) was primarily responsible for the racket velocity in the anteroposterior direction (48.1% CC and 45.2% IO), followed by the extension of the forearm (around the elbow joint) (17.3% CC and 20.9% IO) and the internal rotation of the upper arm (around the shoulder joint) (15.6% CC and 14.2% IO). No significant differences were shown in the contributions of upper limbs to the racket head velocity between the two directions of the shot. Tennis coaches and players should develop a specific training programme to perform higher angular velocities in these specific joint rotations. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensors Methods and Data Analytics)

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12 pages, 5785 KiB

Open AccessArticle

Vision-Based System for Automated Estimation of the Frontal Area of Swimmers: Towards the Determination of the Instant Active Drag: A Pilot Study

by José M. González-Ravé, Francisco Moya-Fernández, Francisco Hermosilla-Perona and Fernando J. Castillo-García

Sensors 2022, 22(3), 955; https://doi.org/10.3390/s22030955 - 26 Jan 2022

Cited by 4 | Viewed by 2217

Abstract

Swimmers take great advantage by reducing the drag forces either in passive or active conditions. The purpose of this work is to determine the frontal area of swimmers by means of an automated vision system. The proposed algorithm is automated and also allows to determine lateral pose of the swimmer for training purposes. In this way, a step towards the determination of the instantaneous active drag is reached that could be obtained by correlating the effective frontal area of the swimmer to the velocity. This article shows a novel algorithm for estimating the frontal and lateral area in comparison with other models. The computing time allows to obtain a reasonable online representation of the results. The development of an automated method to obtain the frontal surface area during swimming increases the knowledge of the temporal fluctuation of the frontal surface area in swimming. It would allow the best monitoring of a swimmer in their swimming training sessions. Further works will present the complete device, which allows to track the swimmer while acquiring the images and a more realistic model of conventional active drag ones. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensors Methods and Data Analytics)

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9 pages, 599 KiB

Open AccessArticle

Does Gait with an Ankle Foot Orthosis Improve or Compromise Minimum Foot Clearance?

by Pedro Fonseca, Leandro Machado, Manoela Vieira Sousa, Ricardo Sebastião, Filipa Sousa, Joana Figueiredo, Cristina P. Santos and João Paulo Vilas-Boas

Sensors 2021, 21(23), 8089; https://doi.org/10.3390/s21238089 - 03 Dec 2021

Cited by 1 | Viewed by 1745

Abstract

The purpose of this study was to investigate if the use of an ankle foot orthosis in passive mode (without actuation) could modify minimum foot clearance, and if there are any compensatory mechanisms to enable these changes during treadmill gait at a constant speed. Eight participants walked on an instrumented treadmill without and with an ankle foot orthosis on the dominant limb at speeds of 0.8, 1.2, and 1.6 km/h. For each gait cycle, the minimum foot clearance and some gait linear kinematic parameters were calculated by an inertial motion capture system. Additionally, maximum hip and knee flexion and maximum ankle plantar flexion were calculated. There were no significant differences in the minimum foot clearance between gait conditions and lower limbs. However, differences were found in the swing, stance and step times between gait conditions, as well as between limbs during gait with orthosis (p < 0.05). An increase in hip flexion during gait with orthosis was observed for all speeds, and different ankle ranges of motion were observed according to speed (p < 0.05). Thus, the use of an ankle foot orthosis in passive mode does not significantly hinder minimum foot clearance, but can change gait linear and angular parameters in non-pathological individuals. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensors Methods and Data Analytics)

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18 pages, 3706 KiB

Open AccessArticle

Low Back Pain—Behavior Correction by Providing Haptic Feedbacks: A Preliminary Investigation

by Andrea Ferrone, Astrid García Patiño and Carlo Menon

Sensors 2021, 21(21), 7158; https://doi.org/10.3390/s21217158 - 28 Oct 2021

Cited by 1 | Viewed by 2105

Abstract

The activities performed by nurses in their daily activities involve frequent forward bending and awkward back postures. These movements contribute to the prevalence and development of low back pain (LBP). In previous studies, it has been shown that modifying their posture by education and training in proper lifting techniques decreases the prevalence of LBP. However, this education and training needs to be implemented daily. Hence, implementing the use of a wearable device to monitor the back posture with haptic feedback would be of importance to prevent LBP. This paper proposes a wearable device to monitor the back posture of the user and provide feedback when the participant is performing a possible hurtful movement. In this study, a group of participants was asked to wear the device while performing three of the most common activities performed by nurses. The study was divided into three sessions: In the first session, the participants performed the activities without feedback (baseline). During the second session, the participants received feedback from the wearable device (training) while performing the three tasks. Finally, for the third session, the participants performed the three tasks again, but the haptic feedback was turned off (validation). We found an improvement in the posture of more than 40% for the pitch (lateral bending) and roll (forward/backward bending) axes and 7% for the yaw (twisting) axis when comparing to the results from session 1 and session 2. The comparison between session 1 and session 3 showed an overall improvement of more than 50% for the pitch (lateral bending) and roll (forward/backward bending) axes and more than 20% for the yaw axis. These results hinted at the impact of the haptic feedback on the participants to correct their posture. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensors Methods and Data Analytics)

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11 pages, 6119 KiB

Open AccessArticle

The Effect of Local Cooling at the Elbow on Nerve Conduction Velocity and Motor Unit Behaviour: An Exploration of a Novel Neurological Assessment

by Jim Richards, Antonin Gechev, Jill Alexander, Liane Macedo, Karen A. May and Steven B. Lindley

Sensors 2021, 21(20), 6703; https://doi.org/10.3390/s21206703 - 09 Oct 2021

Cited by 3 | Viewed by 2391

Abstract

Background: This study aimed to determine the effects of a standard therapeutic cooling protocol using crushed ice on the elbow to explore if changes in the motor unit (MU) firing rates in the first dorsal interosseous (FDI) muscle are comparable to known changes in sensory and motor nerve conduction velocity (NCV) due to a regional temperature drop around a peripheral nerve. Methods: Twelve healthy individuals were assessed before cooling, immediately after cooling, and 15 min of rewarming. Assessments included two standard non-invasive nerve conduction velocity tests and a non-invasive investigation of the MU firing rates using surface electromyography decomposition (dEMG). Results: Repeated ANOVAs showed significant differences in the MU firing rates and NCV between time points (p = 0.01 and p < 0.001). All measures showed significant differences between pre and post cooling and between pre-cooling and 15 min of passive re-warming, however, no changes were seen between post cooling and rewarming except in the sensory NCV, which increased but did not return to the pre-cooled state. Conclusions: This current study showed a significant, temporary, and reversible reduction in ulnar NCV across the elbow in healthy subjects, which was associated with a significant decrease in mean MU firing rates in the FDI muscle. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensors Methods and Data Analytics)

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17 pages, 2866 KiB

Open AccessArticle

Analysis of Postural Instability in the Upright Position on Narrow Platforms and the Interactions with Postural Constraints

by Atsushi Sugama and Akihiko Seo

Sensors 2021, 21(11), 3909; https://doi.org/10.3390/s21113909 - 05 Jun 2021

Cited by 2 | Viewed by 2543

Abstract

Background: Loss of balance is a considerable risk factor for workers while using ladders, because they are required to maintain static postural balance on platforms of a restricted size. This study observed center of mass (CoM) and center of pressure (CoP) behaviors and evaluated the effects of the platform depth (anterior–posterior length) and working postures. Methods: Eleven male participants stood on four platforms with depths ranging from 6 to 15 cm and maintained their positions for 60 s while performing or not performing other tasks (object holding, upward viewing, or both simultaneously). The kinematics were analyzed on the sagittal plane based on the inverse pendulum model. Results: The absolute moving range for the CoP–CoM linearly increased with the decreasing platform depth, and the working postures affected the slopes of the linear fits. The relative range of CoP–CoM displacement on narrow platforms was highly correlated with the subjective sense of instability. Conclusions: Monitoring the CoP is effective for a better understanding and evaluation of static postural balance. This study’s findings contribute to improving the design of work equipment through the use of wider platforms that are robust against the effects of working postures. Full article

(This article belongs to the Special Issue Biomechanical Analysis of Motion and Postural Control: Sensors Methods and Data Analytics)

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