A Bayesian approach for pervasive estimation of breaststroke velocity using a wearable IMU

A ubiquitous assessment of swimming velocity (main metric of the performance) is essential for the coach to provide a tailored feedback to the trainee. We present a probabilistic framework for the data-driven estimation of the swimming velocity at every cycle using a low-cost wearable inertial measurement unit (IMU). The statistical validation of the method on 15 swimmers shows that an average relative error of 0.1 ± 9.6% and high correlation with the tethered reference system (rX,Y=0.91 ) is achievable. Besides, a simple tool to analyze the influence of sacrum kinematics on the performance is provided.

Automatic measurement of key ski jumping phases and temporal events with a wearable system.

We propose a new method, based on inertial sensors, to automatically measure at high frequency the durations of the main phases of ski jumping (i.e. take-off release, take-off, and early flight). The kinematics of the ski jumping movement were recorded by four inertial sensors, attached to the thigh and shank of junior athletes, for 40 jumps performed during indoor conditions and 36 jumps in field conditions. An algorithm was designed to detect temporal events from the recorded signals and to estimate the duration of each phase. These durations were evaluated against a reference camera-based motion capture system and by trainers conducting video observations. The precision for the take-off release and take-off durations (indoor < 39 ms, outdoor = 27 ms) can be considered technically valid for performance assessment. The errors for early flight duration (indoor = 22 ms, outdoor = 119 ms) were comparable to the trainers' variability and should be interpreted with caution. No significant changes in the error were noted between indoor and outdoor conditions, and individual jumping technique did not influence the error of take-off release and take-off. Therefore, the proposed system can provide valuable information for performance evaluation of ski jumpers during training sessions.

Evaluation of a mixed approach combining stationary and wearable systems to monitor gait over long distance.

Thanks to decades of research, gait analysis has become an efficient tool. However, mainly due to the price of the motion capture systems, standard gait laboratories have the capability to measure only a few consecutive steps of ground walking. Recently, wearable systems were proposed to measure human motion without volume limitation. Although accurate, these systems are incompatible with most of existing calibration procedures and several years of research will be necessary for their validation. A new approach consisting of using a stationary system with a small capture volume for the calibration procedure and then to measure gait using a wearable system could be very advantageous. It could benefit from the knowledge related to stationary systems, allow long distance monitoring and provide new descriptive parameters. The aim of this study was to demonstrate the potential of this approach. Thus, a combined system was proposed to measure the 3D lower body joints angles and segmental angular velocities. It was then assessed in terms of reliability towards the calibration procedure, repeatability and concurrent validity. The dispersion of the joint angles across calibrations was comparable to those of stationary systems and good reliability was obtained for the angular velocities. The repeatability results confirmed that mean cycle kinematics of long distance walks could be used for subjects' comparison and pointed out an interest for the variability between cycles. Finally, kinematics differences were observed between participants with different ankle conditions. In conclusion, this study demonstrated the potential of a mixed approach for human movement analysis.

Measurement of the dynamics in ski jumping using a wearable inertial sensor-based system.

Abstract Dynamics is a central aspect of ski jumping, particularly during take-off and stable flight. Currently, measurement systems able to measure ski jumping dynamics (e.g. 3D cameras, force plates) are complex and only available in few research centres worldwide. This study proposes a method to determine dynamics using a wearable inertial sensor-based system which can be used routinely on any ski jumping hill. The system automatically calculates characteristic dynamic parameters during take-off (position and velocity of the centre of mass perpendicular to the table, force acting on the centre of mass perpendicular to the table and somersault angular velocity) and stable flight (total aerodynamic force). Furthermore, the acceleration of the ski perpendicular to the table was quantified to characterise the skis lift at take-off. The system was tested with two groups of 11 athletes with different jump distances. The force acting on the centre of mass, acceleration of the ski perpendicular to the table, somersault angular velocity and total aerodynamic force were different between groups and correlated with the jump distances. Furthermore, all dynamic parameters were within the range of prior studies based on stationary measurement systems, except for the centre of mass mean force which was slightly lower.

Monitoring of posture allocations and activities by a shoe-based wearable sensor.

Monitoring of posture allocations and activities enables accurate estimation of energy expenditure and may aid in obesity prevention and treatment. At present, accurate devices rely on multiple sensors distributed on the body and thus may be too obtrusive for everyday use. This paper presents a novel wearable sensor, which is capable of very accurate recognition of common postures and activities. The patterns of heel acceleration and plantar pressure uniquely characterize postures and typical activities while requiring minimal preprocessing and no feature extraction. The shoe sensor was tested in nine adults performing sitting and standing postures and while walking, running, stair ascent/descent and cycling. Support vector machines (SVMs) were used for classification. A fourfold validation of a six-class subject-independent group model showed 95.2% average accuracy of posture/activity classification on full sensor set and over 98% on optimized sensor set. Using a combination of acceleration/pressure also enabled a pronounced reduction of the sampling frequency (25 to 1 Hz) without significant loss of accuracy (98% versus 93%). Subjects had shoe sizes (US) M9.5-11 and W7-9 and body mass index from 18.1 to 39.4 kg/m2 and thus suggesting that the device can be used by individuals with varying anthropometric characteristics.

A wearable system for multi-segment foot kinetics measurement.

This study aims to design a wearable system for kinetics measurement of multi-segment foot joints in long-distance walking and to investigate its suitability for clinical evaluations. The wearable system consisted of inertial sensors (3D gyroscopes and 3D accelerometers) on toes, forefoot, hindfoot, and shank, and a plantar pressure insole. After calibration in a laboratory, 10 healthy elderly subjects and 12 patients with ankle osteoarthritis walked 50m twice wearing this system. Using inverse dynamics, 3D forces, moments, and power were calculated in the joint sections among toes, forefoot, hindfoot, and shank. Compared to those we previously estimated for a one-segment foot model, the sagittal and transverse moments and power in the ankle joint, as measured via multi-segment foot model, showed a normalized RMS difference of less than 11%, 14%, and 13%, respectively, for healthy subjects, and 13%, 15%, and 14%, for patients. Similar to our previous study, the coronal moments were not analyzed. Maxima-minima values of anterior-posterior and vertical force, sagittal moment, and power in shank-hindfoot and hindfoot-forefoot joints were significantly different between patients and healthy subjects. Except for power, the inter-subject repeatability of these parameters was CMC>0.90 for healthy subjects and CMC>0.70 for patients. Repeatability of these parameters was lower for the forefoot-toes joint. The proposed measurement system estimated multi-segment foot joints kinetics with acceptable repeatability but showed difference, compared to those previously estimated for the one-segment foot model. These parameters also could distinguish patients from healthy subjects. Thus, this system is suggested for outcome evaluations of foot treatments.

Front-crawl instantaneous velocity estimation using a wearable inertial measurement unit.

Monitoring the performance is a crucial task for elite sports during both training and competition. Velocity is the key parameter of performance in swimming, but swimming performance evaluation remains immature due to the complexities of measurements in water. The purpose of this study is to use a single inertial measurement unit (IMU) to estimate front crawl velocity. Thirty swimmers, equipped with an IMU on the sacrum, each performed four different velocity trials of 25 m in ascending order. A tethered speedometer was used as the velocity measurement reference. Deployment of biomechanical constraints of front crawl locomotion and change detection framework on acceleration signal paved the way for a drift-free integration of forward acceleration using IMU to estimate the swimmers velocity. A difference of 0.6 ± 5.4 cm · s(-1) on mean cycle velocity and an RMS difference of 11.3 cm · s(-1) in instantaneous velocity estimation were observed between IMU and the reference. The most important contribution of the study is a new practical tool for objective evaluation of swimming performance. A single body-worn IMU provides timely feedback for coaches and sport scientists without any complicated setup or restraining the swimmer's natural technique.

On-shoe wearable sensors for gait and turning assessment of patients with Parkinson's disease.

Assessment of locomotion through simple tests such as timed up and go (TUG) or walking trials can provide valuable information for the evaluation of treatment and the early diagnosis of people with Parkinson's disease (PD). Common methods used in clinics are either based on complex motion laboratory settings or simple timing outcomes using stop watches. The goal of this paper is to present an innovative technology based on wearable sensors on-shoe and processing algorithm, which provides outcome measures characterizing PD motor symptoms during TUG and gait tests. Our results on ten PD patients and ten age-matched elderly subjects indicate an accuracy ± precision of 2.8 ± 2.4 cm/s and 1.3 ± 3.0 cm for stride velocity and stride length estimation compared to optical motion capture, with the advantage of being practical to use in home or clinics without any discomfort for the subject. In addition, the use of novel spatio-temporal parameters, including turning, swing width, path length, and their intercycle variability, was also validated and showed interesting tendencies for discriminating patients in ON and OFF states and control subjects.

Measurement of multi-segment foot joint angles during gait using a wearable system.

Usually the measurement of multi-segment foot and ankle complex kinematics is done with stationary motion capture devices which are limited to use in a gait laboratory. This study aimed to propose and validate a wearable system to measure the foot and ankle complex joint angles during gait in daily conditions, and then to investigate its suitability for clinical evaluations. The foot and ankle complex consisted of four segments (shank, hindfoot, forefoot, and toes), with an inertial measurement unit (3D gyroscopes and 3D accelerometers) attached to each segment. The angles between the four segments were calculated in the sagittal, coronal, and transverse planes using a new algorithm combining strap-down integration and detection of low-acceleration instants. To validate the joint angles measured by the wearable system, three subjects walked on a treadmill for five minutes at three different speeds. A camera-based stationary system that used a cluster of markers on each segment was used as a reference. To test the suitability of the system for clinical evaluation, the joint angle ranges were compared between a group of 10 healthy subjects and a group of 12 patients with ankle osteoarthritis, during two 50-m walking trials where the wearable system was attached to each subject. On average, over all joints and walking speeds, the RMS differences and correlation coefficients between the angular curves obtained using the wearable system and the stationary system were 1 deg and 0.93, respectively. Moreover, this system was able to detect significant alteration of foot and ankle function between the group of patients with ankle osteoarthritis and the group of healthy subjects. In conclusion, this wearable system was accurate and suitable for clinical evaluation when used to measure the multi-segment foot and ankle complex kinematics during long-distance walks in daily life conditions.

Memory-based scheduling of scientific computing clusters

This study looks at how increased memory utilisation affects throughput and energy consumption in scientific computing, especially in high-energy physics. Our aim is to minimise energy consumed by a set of jobs without increasing the processing time. The earlier tests indicated that, especially in data analysis, throughput can increase over 100% and energy consumption decrease 50% by processing multiple jobs in parallel per CPU core. Since jobs are heterogeneous, it is not possible to find an optimum value for the number of parallel jobs. A better solution is based on memory utilisation, but finding an optimum memory threshold is not straightforward. Therefore, a fuzzy logic-based algorithm was developed that can dynamically adapt the memory threshold based on the overall load. In this way, it is possible to keep memory consumption stable with different workloads while achieving significantly higher throughput and energy-efficiency than using a traditional fixed number of jobs or fixed memory threshold approaches.

FastEpistasis: a high performance computing solution for quantitative trait epistasis.

Motivation: Genome-wide association studies have become widely used tools to study effects of genetic variants on complex diseases. While it is of great interest to extend existing analysis methods by considering interaction effects between pairs of loci, the large number of possible tests presents a significant computational challenge. The number of computations is further multiplied in the study of gene expression quantitative trait mapping, in which tests are performed for thousands of gene phenotypes simultaneously. Results: We present FastEpistasis, an efficient parallel solution extending the PLINK epistasis module, designed to test for epistasis effects when analyzing continuous phenotypes. Our results show that the algorithm scales with the number of processors and offers a reduction in computation time when several phenotypes are analyzed simultaneously. FastEpistasis is capable of testing the association of a continuous trait with all single nucleotide polymorphism ( SNP) pairs from 500 000 SNPs, totaling 125 billion tests, in a population of 5000 individuals in 29, 4 or 0.5 days using 8, 64 or 512 processors.

A novel approach to reducing number of sensing units for wearable gait analysis systems.

Gait analysis methods to estimate spatiotemporal measures, based on two, three or four gyroscopes attached on lower limbs have been discussed in the literature. The most common approach to reduce the number of sensing units is to simplify the underlying biomechanical gait model. In this study, we propose a novel method based on prediction of movements of thighs from movements of shanks. Datasets from three previous studies were used. Data from the first study (ten healthy subjects and ten with Parkinson's disease) were used to develop and calibrate a system with only two gyroscopes attached on shanks. Data from two other studies (36 subjects with hip replacement, seven subjects with coxarthrosis, and eight control subjects) were used for comparison with the other methods and for assessment of error compared to a motion capture system. Results show that the error of estimation of stride length compared to motion capture with the system with four gyroscopes and our new method based on two gyroscopes was close ( -0.8 ±6.6 versus 3.8 ±6.6 cm). An alternative with three sensing units did not show better results (error: -0.2 ±8.4 cm). Finally, a fourth that also used two units but with a simpler gait model had the highest bias compared to the reference (error: -25.6 ±7.6 cm). We concluded that it is feasible to estimate movements of thighs from movements of shanks to reduce number of needed sensing units from 4 to 2 in context of ambulatory gait analysis.