Accelerometer based human joints' range of movement measurement

Accurate measurement and analysis of joints' range of movement (ROM) are important for assessing joint related health conditions and are valuable to clinicians for diagnostic and rehabilitation purposes. As an alternative to using the camera-based methods which are restrictive and expensive, and the electro-goniometers which are not sufficiently effective in some scenarios, researchers are developing the use of microelectromechanical devices such as accelerometers for measuring human joints movement. This paper presents the development of an accelerometer based system to measure movement angle, velocity, acceleration and displacement for the knee

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

Detection of static and dynamic activities using uniaxial accelerometers

Rehabilitation treatment may be improved by objective analysis of activities of daily living. For this reason, the feasibility of distinguishing several static and dynamic activities (standing, sitting, lying, walking, ascending stairs, descending stairs, cycling) using a small set of two or three uniaxial accelerometers mounted on the body was investigated. The accelerometer signals can be measured with a portable data acquisition system, which potentially makes it possible to perform online detection of static and dynamic activities in the home environment. However, the procedures described in this paper have yet to be evaluated in the home environment. Experiments were conducted on ten healthy subjects, with accelerometers mounted on several positions and orientations on the body, performing static and dynamic activities according to a fixed protocol. Specifically, accelerometers on the sternum and thigh were evaluated. These accelerometers were oriented in the sagittal plane, perpendicular to the long axis of the segment (tangential), or along this axis (radial). First, discrimination between the static or dynamic character of activities was investigated. This appeared to be feasible using an rms-detector applied on the signal of one sensor tangentially mounted on the thigh. Second, the distinction between static activities was investigated. Standing, sitting, lying supine, on a side and prone could be distinguished by observing the static signals of two accelerometers, one mounted tangentially on the thigh, and the second mounted radially on the sternum. Third, the distinction between the cyclical dynamic activities walking, stair ascent, stair descent and cycling was investigated. The discriminating potentials of several features of the accelerometer signals were assessed: the mean value, the standard deviation, the cycle time and the morphology. Signal morphology was expressed by the maximal cross-correlation coefficients with template signals for the different dynamic activities. The mean signal values and signal morphology of accelerometers mounted tangentially on the thigh and the sternum appeared to contribute to the discrimination of dynamic activities with varying detection performances. The standard deviation of the signal and the cycle time were primarily related to the speed of the dynamic activities, and did not contribute to the discrimination of the activities. Therefore, discrimination of dynamic activities on the basis of the combined evaluation of the mean signal value and signal morphology is propose

Accuracy assessment of Tri-plane B-mode ultrasound for non-invasive 3D kinematic analysis of knee joints

BACKGROUND Currently the clinical standard for measuring the motion of the bones in knee joints with sufficient precision involves implanting tantalum beads into the bones. These beads appear as high intensity features in radiographs and can be used for precise kinematic measurements. This procedure imposes a strong coupling between accuracy and invasiveness. In this paper, a tri-plane B-mode ultrasound (US) based non-invasive approach is proposed for use in kinematic analysis of knee joints in 3D space. METHODS The 3D analysis is performed using image processing procedures on the 2D US slices. The novelty of the proposed procedure and its applicability to the unconstrained 3D kinematic analysis of knee joints is outlined. An error analysis for establishing the method's feasibility is included for different artificial compositions of a knee joint phantom. Some in-vivo and in-vitro scans are presented to demonstrate that US scans reveal enough anatomical details, which further supports the experimental setup used using knee bone phantoms. RESULTS The error between the displacements measured by the registration of the US image slices and the true displacements of the respective slices measured using the precision mechanical stages on the experimental apparatus is evaluated for translation and rotation in two simulated environments. The mean and standard deviation of errors are shown in tabular form. This method provides an average measurement precision of less than 0.1 mm and 0.1 degrees, respectively. CONCLUSION In this paper, we have presented a novel non-invasive approach to measuring the motion of the bones in a knee using tri-plane B-mode ultrasound and image registration. In our study, the image registration method determines the position of bony landmarks relative to a B-mode ultrasound sensor array with sub-pixel accuracy. The advantages of our proposed system over previous techniques are that it is non-invasive, does not require the use of ionizing radiation and can be used conveniently if miniaturized.This work has been supported by School of Engineering & IT, UNSW Canberra, under Research Publication Fellowship

A new multisensor software architecture for movement detection: Preliminary study with people with cerebral palsy

A five-layered software architecture translating movements into mouse clicks has been developed and tested on an Arduino platform with two different sensors: accelerometer and flex sensor. The archi-tecture comprises low-pass and derivative filters, an unsupervised classifier that adapts continuously to the strength of the user's movements and a finite state machine which sets up a timer to prevent in-voluntary movements from triggering false positives. Four people without disabilities and four people with cerebral palsy (CP) took part in the experi-ments. People without disabilities obtained an average of 100% and 99.3% in precision and true positive rate (TPR) respectively and there were no statistically significant differences among type of sensors and placement. In the same experiment, people with disabilities obtained 97.9% and 100% in precision and TPR respectively. However, these results worsened when subjects used the system to access a commu-nication board, 89.6% and 94.8% respectively. With their usual method of access-an adapted switch- they obtained a precision and TPR of 86.7% and 97.8% respectively. For 3-outof- 4 participants with disabilities our system detected the movement faster than the switch. For subjects with CP, the accelerometer was the easiest to use because it is more sensitive to gross motor motion than the flex sensor which requires more complex movements. A final survey showed that 3-out-of-4 participants with disabilities would prefer to use this new technology instead of their tra-ditional method of access

Inertial measurement techniques for human joints' movement analysis

Abstract. Development and assessment of techniques that allow inertia measurement units consisting of an accelerometer and a gyroscope to be used for monitoring human joints' movements are presented. A new wavelet packet decomposition technique was developed that denoised the accelerometer signals. Investigations on the use of accelerometers to analyse legs’ movements are described

Assessment of hand kinematics using inertial and magnetic sensors

Background:\ud Assessment of hand kinematics is important when evaluating hand functioning. Major drawbacks ofcurrent sensing glove systems are lack of rotational observability in particular directions, labourintensive calibration methods which are sensitive to wear and lack of an absolute hand orientationestimate.\ud \ud Methods:\ud We propose an ambulatory system using inertial sensors that can be placed on the hand, fingers andthumb. It allows a full 3D reconstruction of all finger and thumb joints as well as the absoluteorientation of the hand. The system was experimentally evaluated for the static accuracy, dynamicrange and repeatability.\ud \ud Results:\ud The RMS position norm difference of the fingertip compared to an optical system was 5±0.5 mm(mean ± standard deviation) for flexion-extension and 12.4±3.0 mm for combined flexion-extensionabduction-adduction movements of the index finger. The difference between index and thumb tipsduring a pinching movement was 6.5±2.1 mm. The dynamic range of the sensing system and filterwas adequate to reconstruct full 80 degrees movements of the index finger performed at 116 timesper minute, which was limited by the range of the gyroscope. Finally, the reliability study showed amean range difference over five subjects of 1.1±0.4 degrees for a flat hand test and1.8±0.6 degrees for a plastic mold clenching test, which is smaller than other reported data gloves.\ud \ud Conclusion:\ud Compared to existing data gloves, this research showed that inertial and magnetic sensors are of interest for ambulatory analysis of the human hand and finger kinematics in terms of static accuracy, dynamic range and repeatability. It allows for estimation of multi-degree of freedom joint movements using low-cost sensors