Wearables for disabled and extreme sports

Sensors

The standard technology used to capture motion for biomechanical analysis in sports has employed marker-based optical systems. While these systems are excellent at providing positional information, they suffer from a limited ability to accurately provide fundamental quantities such as velocity and acceleration (hence forces and torques) during high-speed motion typical of many sports. Conventional optical systems require considerable setup time, can exhibit sensitivity to extraneous light, and generally sample too slowly to accurately capture extreme bursts of athletic activity. In recent years, wireless wearable sensors have begun to penetrate devices used in sports performance assessment, offering potential solutions to these limitations. This article, after determining pressing problems in sports that such sensors could solve and surveying the state-of-the-art in wearable motion capture for sports, presents a wearable dual-range inertial and magnetic sensor platform that we devel...

2009

Gait & Posture, 2008

Background and aims: In many applications, it is essential that the evaluation of a given motor task is not affected by the restrictions of the laboratory environment. To accomplish this requirement, miniature triaxial inertial and magnetic sensors can be used. This paper describes an anatomical calibration technique for wearable inertial and magnetic sensing modules based on the direct measure of the direction of anatomical axes using palpable anatomical landmarks. An anatomical frame definition for the estimate of joint angular kinematics of the lower limb is also proposed. Methods: The performance of the methodology was evaluated in an upright posture and a walking trial of a single able-bodied subject. The repeatability was assessed with six examiners performing the anatomical calibration, while its consistency was evaluated by comparing the results with those obtained using stereophotogrammetry. Results: Results relative to the up-right posture trial revealed an intra-and inter-examiner variability which is minimal in correspondence to the flex-extension angles (0.2-2.98) and maximal to the internal-external rotation (1.6-7.38). For the level walking, the root mean squared error between the kinematics estimated with the two measurement techniques varied from 2.5% to 4.8% of the range of motion for the flexextension, whereas it ranged from 13.1% to 41.8% in correspondence of the internal-external rotation. Conclusion: The proposed methodology allowed for the estimate of lower limb joint angular kinematics in a repeatable and consistent manner, enabling inertial and magnetic sensing based systems to be used especially for outdoor human movement analysis applications. #

— Existing human body motion capture solutions rely on camera based systems limited to confined measurements, or Inertial Measurement Units (IMUs) prone to noise and drift, resulting in position inaccuracies. This investigation demonstrates a proof-of-concept wearable sensor system which accurately monitors human body kinematics in real-time using Radio Frequency (RF) positioning sensors combined with MEMS based IMU sensors. In certain IMU orientations, we measured an average pitch error of < 2 degrees for the combined method, compared with 12 degrees for an IMU alone. This self-contained sensor network has applications including military training, gaming, sports and healthcare.

2018

Physical activity monitoring is important to record all the daily physical activities for the purpose of fitness and health. This motive caused a tremendous progress in the wearable technologies. Current project encompasses 9 degree of freedom inertial sensor (triaxial accelerometer, gyroscope, and magnetometer) with Wi-Fi communication in a very small wearable data logger integrated with a web server. It is applicable as on-body sensor network for more intricate activity recognition applications. Inertial sensor data measured and transferred to either a custom designed web server in online mode or stored in a MicroSD memory card in the offline mode. Wearable data logger with 18×30×30 mm (W×L×H) and 20 grams weight designed and produced. The system was tested at 200 Hz during online mode and acceptable precision and noise ascertained. Current device provided movement recording with wireless communication in small size and low cost to be applicable in the health and fitness applicati...

2013

Fully mobile and wireless motion capturing is a mandatory requirement for undisturbed and non-reactive analysis of human movements. Therefore, inertial sensor platforms are used in applications like analysis of training sessions in sports or rehabilitation, and allow non-restricted motion capturing. The computation of the required reliable orientation estimation based on the inertial sensor RAW data is a demanding computational task. Highly customized and thus low-power wearable computation platforms require low-level, platform independent communication protocols and connectivity. State-of-the-art small sized commercial inertial sensors either lack the availability of an open, platform independent protocol, wireless connectivity or extension interfaces for additional sensors. Therefore, a extensible, wireless inertial sensor called (IM) 2 SU * , featuring onboard inertial sensor fusion, for use in home based stroke rehabilitation is proposed. To evaluate orientation estimation accuracy an optical system is used as golden reference. The proposed IMU provides high orientation estimation accuracy, low costs, a platform independent, wireless connection and extensibility.

PloS one, 2018

Inertial sensors offer the potential for integration into wireless virtual reality systems that allow the users to walk freely through virtual environments. However, owing to drift errors, inertial sensors cannot accurately estimate head and body orientations in the long run, and when walking indoors, this error cannot be corrected by magnetometers, due to the magnetic field distortion created by ferromagnetic materials present in buildings. This paper proposes a technique, called EHBD (Equalization of Head and Body Directions), to address this problem using two head- and shoulder-located magnetometers. Due to their proximity, their distortions are assumed to be similar and the magnetometer measurements are used to detect when the user is looking straight forward. Then, the system corrects the discrepancies between the estimated directions of the head and the shoulder, which are provided by gyroscopes and consequently are affected by drift errors. An experiment is conducted to evalu...

Magnetic and inertial measurement units are an emerging technology to obtain 3D orientation of body segments in human movement analysis. In this respect, sensor fusion is used to limit the drift errors resulting from the gyroscope data integration by exploiting accelerometer and magnetic aiding sensors. The present study aims at investigating the effectiveness of sensor fusion methods under different experimental conditions. Manual and locomotion tasks, differing in time duration, measurement volume, presence/absence of static phases, and out-of-plane movements, were performed by six subjects, and recorded by one unit located on the forearm or the lower trunk, respectively. Two sensor fusion methods, representative of the stochastic (Extended Kalman Filter) and complementary (Non-linear observer) filtering, were selected, and their accuracy was assessed in terms of attitude (pitch and roll angles) and heading (yaw angle) errors using stereophotogrammetric data as a reference. The sensor fusion approaches provided significantly more accurate results than gyroscope data integration. Accuracy improved mostly for heading and when the movement exhibited stationary phases, evenly distributed 3D rotations, it occurred in a small volume, and its duration was greater than approximately 20 s. These results were independent from the specific sensor fusion method used. Practice guidelines for improving the outcome accuracy are provided.

2011 IEEE SENSORS Proceedings, 2011

In this paper, we overview recent work from our research group that explores two very different applications of wearable inertial systems. The first project exploits an array of wearable, ultrawide-range, synchronous IMUs to measure the performance of professional baseball players. We describe some special aspects of our hardware (a dual-range, 6-DOF IMU with magnetometer), and show sample data from our current analysis. We also overview another project where we leveraged wearable sensors, including a micropower integrating accelerometer, for mobile personalized comfort control of building HVAC (heating/air conditioning) systems. I.

IFAC-PapersOnLine, 2020

To capture human motion with inertial sensors, they are attached as a network on different segments. Typically the measurements received from each sensor are fused to obtain its orientation. A challenging task is to align the orientation of each sensor w.r.t. to a single common coordinate frame. To fulfill this task typically the local magnetic field is measured to provide information about the heading direction. Since especially in indoor environments magnetic field disturbances can be present, this information is not a reliable source. To overcome this problem, we present a method that aligns an on-body inertial sensor network using gyroscopes and accelerometers only. The subject wearing the network had to fulfill a predefined procedure, consisting of standing still and walking straight. To extract the heading direction, we estimated the linear acceleration and angular velocity using a maximum-a-posteriori estimator. Performing a principal component analysis on the estimated states we computed two heading directions for each estimate. Instead of using them separately, we used a fusing approach that exploits symmetrical effects. We validated the approach on a lower body configuration using an optical motion capture system. The heading direction of sensors attached on a single leg could be aligned up to median maximal deviation of 2.6 degrees and on the complete lower body of 6.6 degrees. Especially deviations of the pelvis were higher, due to a lack of motion excitation. To be able to quantify the excitation needed, we proposed an indicator based on the ratio of the eigenvalues of the principal component analysis of the angular velocities.