Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion

Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environments. After a survey on IMU-based human tracking, five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion. IMU based estimation was matched against motion tracking based on the Vicon marker-based motion tracking system considered as ground truth. Results show that all but one of the selected models perform similarly (about 35 mm average position estimation error)

A Comparison of Video and Accelerometer Based Approaches Applied to Performance Monitoring in Swimming.

The aim of this paper is to present a comparison of video- and sensor based studies of swimming performance. The video-based approach is reviewed and contrasted to the newer sensor-based technology, specifically accelerometers based upon Micro-Electro-Mechanical Systems (MEMS) technology. Results from previously published swim performance studies using both the video and sensor technologies are summarised and evaluated against the conventional theory that upper arm movements are of primary interest when quantifying free-style technique. The authors conclude that multiple sensor-based measurements of swimmers’ acceleration profiles have the potential to offer significant advances in coaching technique over the traditional video based approach

Development of a mobile technology system to measure shoulder range of motion

In patients with shoulder movement impairment, assessing and monitoring shoulder range of motion is important for determining the severity of impairments due to disease or injury and evaluating the effects of interventions. Current clinical methods of goniometry and visual estimation require an experienced user and suffer from low inter-rater reliability. More sophisticated techniques such as optical or electromagnetic motion capture exist but are expensive and restricted to a specialised laboratory environment.;Inertial measurement units (IMU), such as those within smartphones and smartwatches, show promise as tools bridge the gap between laboratory and clinical techniques and accurately measure shoulder range of motion during both clinic assessments and in daily life.;This study aims to develop an Android mobile application for both a smartphone and a smartwatch to assess shoulder range of motion. Initial performance characterisation of the inertial sensing capabilities of both a smartwatch and smartphone running the application was conducted against an industrial inclinometer, free-swinging pendulum and custom-built servo-powered gimbal.;An initial validation study comparing the smartwatch application with a universal goniometer for shoulder ROM assessment was conducted with twenty healthy participants. An impaired condition was simulated by applying kinesiology tape across the participants shoulder girdle. Agreement, intra and inter-day reliability were assessed in both the healthy and impaired states.;Both the phone and watch performed with acceptable accuracy and repeatability during static (within ±1.1°) and dynamic conditions where it was strongly correlated to the pendulum and gimbal data (ICC > 0.9). Both devices could perform accurately within optimal responsiveness range of angular velocities compliant with humerus movement during activities of daily living (frequency response of 377°/s and 358°/s for the phone and watch respectively).;The concurrent agreement between the watch and the goniometer was high in both healthy and impaired states (ICC > 0.8) and between measurement days (ICC > 0.8). The mean absolute difference between the watch and the goniometer were within the accepted minimal clinically important difference for shoulder movement (5.11° to 10.58°).;The results show promise for the use of the developed Android application to be used as a goniometry tool for assessment of shoulder ROM. However, the limits of agreement across all the tests fell out with the acceptable margin and further investigation is required to determine validity. Evaluation of validity in clinical impairment patients is also required to assess the feasibility of the use of the application in clinical practice.In patients with shoulder movement impairment, assessing and monitoring shoulder range of motion is important for determining the severity of impairments due to disease or injury and evaluating the effects of interventions. Current clinical methods of goniometry and visual estimation require an experienced user and suffer from low inter-rater reliability. More sophisticated techniques such as optical or electromagnetic motion capture exist but are expensive and restricted to a specialised laboratory environment.;Inertial measurement units (IMU), such as those within smartphones and smartwatches, show promise as tools bridge the gap between laboratory and clinical techniques and accurately measure shoulder range of motion during both clinic assessments and in daily life.;This study aims to develop an Android mobile application for both a smartphone and a smartwatch to assess shoulder range of motion. Initial performance characterisation of the inertial sensing capabilities of both a smartwatch and smartphone running the application was conducted against an industrial inclinometer, free-swinging pendulum and custom-built servo-powered gimbal.;An initial validation study comparing the smartwatch application with a universal goniometer for shoulder ROM assessment was conducted with twenty healthy participants. An impaired condition was simulated by applying kinesiology tape across the participants shoulder girdle. Agreement, intra and inter-day reliability were assessed in both the healthy and impaired states.;Both the phone and watch performed with acceptable accuracy and repeatability during static (within ±1.1°) and dynamic conditions where it was strongly correlated to the pendulum and gimbal data (ICC > 0.9). Both devices could perform accurately within optimal responsiveness range of angular velocities compliant with humerus movement during activities of daily living (frequency response of 377°/s and 358°/s for the phone and watch respectively).;The concurrent agreement between the watch and the goniometer was high in both healthy and impaired states (ICC > 0.8) and between measurement days (ICC > 0.8). The mean absolute difference between the watch and the goniometer were within the accepted minimal clinically important difference for shoulder movement (5.11° to 10.58°).;The results show promise for the use of the developed Android application to be used as a goniometry tool for assessment of shoulder ROM. However, the limits of agreement across all the tests fell out with the acceptable margin and further investigation is required to determine validity. Evaluation of validity in clinical impairment patients is also required to assess the feasibility of the use of the application in clinical practice

Tracking of Human Joints Using Twist and Exponential Map

Motion tracking system in the home-based environment exhibits attractive advantages for stroke patients. Current methods suffer from incapability of accurately tracking movements with high degree of freedoms. Besides hardly meeting the predefined position during inertial sensor mounting also affects system\u27s performance. To tackle these challenges, a motion tracking system using twist and exponential map technology is developed in this paper. Firstly, a kinematic model for trunk and upper extremity is designed. Based on this model, twist and exponential map method which updates frames in their initial coordinates instead of transforming coordinates from one frame to another presents high efficiency and convenience in estimating joints\u27 position and orientation. In the experiment, multiple movements are tracked by both of inertial sensor system and optical tracking system. Their comparison verifies this system\u27s high accuracy

Wearable inertial sensors for human movement analysis

Introduction: The present review aims to provide an overview of the most common uses of wearable inertial sensors in the field of clinical human movement analysis.Areas covered: Six main areas of application are analysed: gait analysis, stabilometry, instrumented clinical tests, upper body mobility assessment, daily-life activity monitoring and tremor assessment. Each area is analyzed both from a methodological and applicative point of view. The focus on the methodological approaches is meant to provide an idea of the computational complexity behind a variable/parameter/index of interest so that the reader is aware of the reliability of the approach. The focus on the application is meant to provide a practical guide for advising clinicians on how inertial sensors can help them in their clinical practice.Expert commentary: Less expensive and more easy to use than other systems used in human movement analysis, wearable sensors have evolved to the point that they can be considered ready for being part of routine clinical routine

Custom IMU-Based Wearable System for Robust 2.4 GHz Wireless Human Body Parts Orientation Tracking and 3D Movement Visualization on an Avatar

Recent studies confirm the applicability of Inertial Measurement Unit (IMU)-based systems for human motion analysis. Notwithstanding, high-end IMU-based commercial solutions are yet too expensive and complex to democratize their use among a wide range of potential users. Less featured entry-level commercial solutions are being introduced in the market, trying to fill this gap, but still present some limitations that need to be overcome. At the same time, there is a growing number of scientific papers using not commercial, but custom do-it-yourself IMU-based systems in medical and sports applications. Even though these solutions can help to popularize the use of this technology, they have more limited features and the description on how to design and build them from scratch is yet too scarce in the literature. The aim of this work is two-fold: (1) Proving the feasibility of building an affordable custom solution aimed at simultaneous multiple body parts orientation tracking; while providing a detailed bottom-up description of the required hardware, tools, and mathematical operations to estimate and represent 3D movement in real-time. (2) Showing how the introduction of a custom 2.4 GHz communication protocol including a channel hopping strategy can address some of the current communication limitations of entry-level commercial solutions. The proposed system can be used for wireless real-time human body parts orientation tracking with up to 10 custom sensors, at least at 50 Hz. In addition, it provides a more reliable motion data acquisition in Bluetooth and Wi-Fi crowded environments, where the use of entry-level commercial solutions might be unfeasible. This system can be used as a groundwork for developing affordable human motion analysis solutions that do not require an accurate kinematic analysis.This research has been partially funded by a research contract with IVECO Spain SL and by the Department of Employment and Industry of Castilla y León (Spain), under research project ErgoTwyn (INVESTUN/21/VA/0003)

Ambulatory position and orientation tracking fusing magnetic and inertial sensing

This paper presents the design and testing of a portable magnetic system combined with miniature inertial sensors for ambulatory 6 degrees of freedom ( DOF) human motion tracking. The magnetic system consists of three orthogonal coils, the source, fixed to the body and 3-D magnetic sensors, fixed to remote body segments, which measure the fields generated by the source. Based on the measured signals, a processor calculates the relative positions and orientations between source and sensor. Magnetic actuation requires a substantial amount of energy which limits the update rate with a set of batteries. Moreover, the magnetic field can easily be disturbed by ferromagnetic materials or other sources. Inertial sensors can be sampled at high rates, require only little energy and do not suffer from magnetic interferences. However, accelerometers and gyroscopes can only measure changes in position and orientation and suffer from integration drift. By combing measurements from both systems in a complementary Kalman filter structure, an optimal solution for position and orientation estimates is obtained. The magnetic system provides 6 DOF measurements at a relatively low update rate while the inertial sensors track the changes position and orientation in between the magnetic updates. The implemented system is tested against a lab-bound camera tracking system for several functional body movements. The accuracy was about 5 mm for position and 3 degrees for orientation measurements. Errors were higher during movements with high velocities due to relative movement between source and sensor within one cycle of magnetic actuation

A bi-articular model for scapular-humeral rhythm reconstruction through data from wearable sensors

Patient-specific performance assessment of arm movements in daily life activities is fundamental for neurological rehabilitation therapy. In most applications, the shoulder movement is simplified through a socket-ball joint, neglecting the movement of the scapular-thoracic complex. This may lead to significant errors. We propose an innovative bi-articular model of the human shoulder for estimating the position of the hand in relation to the sternum. The model takes into account both the scapular-toracic and gleno-humeral movements and their ratio governed by the scapular-humeral rhythm, fusing the information of inertial and textile-based strain sensors

Measurement of Upper Limb Range of Motion Using Wearable Sensors: A Systematic Review.

Background: Wearable sensors are portable measurement tools that are becoming increasingly popular for the measurement of joint angle in the upper limb. With many brands emerging on the market, each with variations in hardware and protocols, evidence to inform selection and application is needed. Therefore, the objectives of this review were related to the use of wearable sensors to calculate upper limb joint angle. We aimed to describe (i) the characteristics of commercial and custom wearable sensors, (ii) the populations for whom researchers have adopted wearable sensors, and (iii) their established psychometric properties. Methods: A systematic review of literature was undertaken using the following data bases: MEDLINE, EMBASE, CINAHL, Web of Science, SPORTDiscus, IEEE, and Scopus. Studies were eligible if they met the following criteria: (i) involved humans and/or robotic devices, (ii) involved the application or simulation of wearable sensors on the upper limb, and (iii) calculated a joint angle. Results: Of 2191 records identified, 66 met the inclusion criteria. Eight studies compared wearable sensors to a robotic device and 22 studies compared to a motion analysis system. Commercial (n = 13) and custom (n = 7) wearable sensors were identified, each with variations in placement, calibration methods, and fusion algorithms, which were demonstrated to influence accuracy. Conclusion: Wearable sensors have potential as viable instruments for measurement of joint angle in the upper limb during active movement. Currently, customised application (i.e. calibration and angle calculation methods) is required to achieve sufficient accuracy (error < 5°). Additional research and standardisation is required to guide clinical application

A hybrid modified group method of data handling with the wavelet decomposition for oil palm price forecasting

This thesis presents an exploratory study on hybrid modelling of palm oil price forecasting using modified group method of data handling (GMDH) network with the discrete wavelet transform (DWT) approach. Despite the fact that Malaysia is one of the largest producer and exporter of palm oil, the research on modelling of palm oil price forecasting is still in progress. This study comprises by exploring the appropriate models for forecasting the monthly palm oil price such as conventional GMDH, modified GMDH and hybrid wavelet modified GMDH models. To assess the effectiveness of these models, monthly crude palm oil (CPO) price of Malaysia from January 1983 until November 2019 and Pakistan from September 2001 until June 2019 were used as sample study. The study shows that modified GMDH model, which integrates four transfer functions such as radial basis, sigmoid, tangent and polynomial simultaneously into GMDH, has given the best fit for modelling of palm oil price forecasting as compared to conventional GMDH model. However, the individual model is not best every time to achieve the better results. In improving the model, this study explores a hybrid wavelet modified GMDH model. The architecture of the proposed hybrid model includes DWT, which is selected as a preprocessed clean and pure data enabling the modified GMDH network to present itself as a well-established alternative application to predict the future of CPO. The proposed hybrid model has been applied to different CPO data sets and verified using simulation of different splits of model input data series. Comparative studies among various models were carried out. The mean absolute percentage error (MAPE) of the proposed hybrid model for the monthly CPO price of Malaysia is less than 4 % and coefficient of correlation (R) is 0.99, which show an excellent fit as compared to the individual and other benchmark models. Similarly, the MAPE of hybrid model for Pakistan imports monthly CPO is less than 14 % and R is 0.94, which show good fit as compared to the individual and other benchmark models. The results have demonstrated that the proposed hybrid model is a better alternative model for crude palm oil price forecastin