7,588 research outputs found
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
Human Gait Model Development for Objective Analysis of Pre/Post Gait Characteristics Following Lumbar Spine Surgery
Although multiple advanced tools and methods are available for gait analysis, the gait and its related disorders are usually assessed by visual inspection in the clinical environment. This thesis aims to introduce a gait analysis system that provides an objective method for gait evaluation in clinics and overcomes the limitations of the current gait analysis systems. Early identification of foot drop, a common gait disorder, would become possible using the proposed methodology
Objective assessment of movement disabilities using wearable sensors
The research presents a series of comprehensive analyses based on inertial measurements obtained from wearable sensors to quantitatively describe and assess human kinematic performance in certain tasks that are most related to daily life activities. This is not only a direct application of human movement analysis but also very pivotal in assessing the progression of patients undergoing rehabilitation services. Moreover, the detailed analysis will provide clinicians with greater insights to capture movement disorders and unique ataxic features regarding axial abnormalities which are not directly observed by the clinicians
Detection of postural transitions using machine learning
The purpose of this project is to study the nature of human activity recognition and prepare a dataset from volunteers doing various activities which can be used for constructing the various parts of a machine learning model which is used to identify each volunteers posture transitions accurately. This report presents the problem definition, equipment used, previous work in this area of human activity recognition and the resolution of the problem along with results. Also this report sheds light on the process and the steps taken to undertake this endeavour of human activity recognition such as building of a dataset, pre-processing the data by applying filters and various windowing length techniques, splitting the data into training and testing data, performance of feature selection and feature extraction and finally selecting the model for training and testing which provides maximum accuracy and least misclassification rates. The tools used for this project includes a laptop equipped with MATLAB and EXCEL and MEDIA PLAYER CLASSIC respectively which have been used for data processing, model training and feature selection and Labelling respectively. The data has been collected using an Inertial Measurement Unit contains 3 tri-axial Accelerometers, 1 Gyroscope, 1 Magnetometer and 1 Pressure sensor. For this project only the Accelerometers, Gyroscope and the Pressure sensor is used. The sensor is made by the members of the lab named ‘The Technical Research Centre for Dependency Care and Autonomous Living (CETpD) at the UPC-ETSEIB campus. The results obtained have been satisfactory, and the objectives set have been fulfilled. There is room for possible improvements through expanding the scope of the project such as detection of chronic disorders or providing posture based statistics to the end user or even just achieving a higher rate of sensitivity of transitions of posture by using better features and increasing the dataset size by increasing the number of volunteers.Incomin
Implementing and Evaluating a Wireless Body Sensor System for Automated Physiological Data Acquisition at Home
Advances in embedded devices and wireless sensor networks have resulted in
new and inexpensive health care solutions. This paper describes the
implementation and the evaluation of a wireless body sensor system that
monitors human physiological data at home. Specifically, a waist-mounted
triaxial accelerometer unit is used to record human movements. Sampled data are
transmitted using an IEEE 802.15.4 wireless transceiver to a data logger unit.
The wearable sensor unit is light, small, and consumes low energy, which allows
for inexpensive and unobtrusive monitoring during normal daily activities at
home. The acceleration measurement tests show that it is possible to classify
different human motion through the acceleration reading. The 802.15.4 wireless
signal quality is also tested in typical home scenarios. Measurement results
show that even with interference from nearby IEEE 802.11 signals and microwave
ovens, the data delivery performance is satisfactory and can be improved by
selecting an appropriate channel. Moreover, we found that the wireless signal
can be attenuated by housing materials, home appliances, and even plants.
Therefore, the deployment of wireless body sensor systems at home needs to take
all these factors into consideration.Comment: 15 page
Sparse Inertial Poser: Automatic 3D Human Pose Estimation from Sparse IMUs
We address the problem of making human motion capture in the wild more
practical by using a small set of inertial sensors attached to the body. Since
the problem is heavily under-constrained, previous methods either use a large
number of sensors, which is intrusive, or they require additional video input.
We take a different approach and constrain the problem by: (i) making use of a
realistic statistical body model that includes anthropometric constraints and
(ii) using a joint optimization framework to fit the model to orientation and
acceleration measurements over multiple frames. The resulting tracker Sparse
Inertial Poser (SIP) enables 3D human pose estimation using only 6 sensors
(attached to the wrists, lower legs, back and head) and works for arbitrary
human motions. Experiments on the recently released TNT15 dataset show that,
using the same number of sensors, SIP achieves higher accuracy than the dataset
baseline without using any video data. We further demonstrate the effectiveness
of SIP on newly recorded challenging motions in outdoor scenarios such as
climbing or jumping over a wall.Comment: 12 pages, Accepted at Eurographics 201
Body sensor network for in-home personal healthcare
A body sensor network solution for personal healthcare under an indoor environment is developed. The system is capable of logging the physiological signals of human beings, tracking the orientations of human body, and monitoring the environmental attributes, which covers all necessary information for the personal healthcare in an indoor environment.
The major three chapters of this dissertation contain three subsystems in this work, each corresponding to one subsystem: BioLogger, PAMS and CosNet. Each chapter covers the background and motivation of the subsystem, the related theory, the hardware/software design, and the evaluation of the prototype’s performance
- …