A possible anatomical and biomechanical explanation of the 10% rule used in the clinical assessment of prehensile hand movements and handed dominance

Abstract
A current doctrine in the dynamometric approach to determine lateralization of hand function states that in 10% of cases, the non-dominant hand will be stronger than the dominant hand. In this study, a novel MRI based modelling approach was applied to the first dorsal introsseus muscle (FDI), to determine whether the 10% rule may be applied to the FDI and may be partially explained by the arrangement of the anatomical components of the FDI.

Methods
Initially the force generated by the thumb segment during an isometric pushing task in the horizontal plane was measured from 25 strongly right-handed young males. Nine of these participants then had structural magnetic resonance imaging (sMRI) of the thumb and index osseous compartment. A modelling technique was developed to extract the muscle data and quantify the muscle line of action onto to the first metacarpal bone segment in order to quantify the muscle force at the point of momentary rotation – equilibrium.

Results
Eight of 25 subjects exhibited stronger force from the left hand. Six out of nine subjects from the MRI possessed significantly greater angles of attachment of the index osseous compartment on the left (non-dominant) hand. These six subjects also generated greater maximal isometric forces from the FDI of the left side. There was a significantly greater muscle volume for the right FDI muscle as compared to the left as measured from the reconstructed MRI slice data.

Conclusions
The calculated force produced by the muscle is related to the angle of attachment of the muscle to bone in the index osseous compartment. The MRI findings indicate that the 10% rule may be anatomically and biomechanically explained.

Kinematic analysis and workspace determination of hexarot-a novel 6-DOF parallel manipulator with a rotation-symmetric arm system

Parallel mechanisms possess several advantages such as the possibilities for high acceleration and high accuracy positioning of the end effector. However, most of the proposed parallel manipulators suffer from a limited workspace. In this paper, a novel 6-DOF parallel manipulator with coaxial actuated arms is introduced. Since parallel mechanisms have more workspace limitations compared to that of serial mechanisms, determination of the workspace in parallel manipulators is of the utmost importance. For finding position, angular velocity, and acceleration, in this paper, inverse and forward kinematics of the mechanism are studied and after presenting the workspace limitations, workspace analysis of the hexarot manipulator is performed by using MATLAB software. Next, using the obtained cloud of points from simulation, the overall borders of the workspace are illustrated. Finally, it is shown that this manipulator has the important benefits of combining a large positional workspace in relation to its footprint with a sizable range of platform rotations.

Changes in quality of life associated with fragility fractures: Australian arm of the International Cost and Utility Related to Osteoporotic Fractures Study (AusICUROS).

We investigated change in health-related quality of life due to fracture in Australian adults aged over 50 years. Fractures reduce quality of life with the loss sustained at least over 12 months. At a population level, the loss was equivalent to 65 days in full health per fracture.

Teleoperation of ABB industrial robots

Purpose - The purpose of this paper is to analyse teleoperation of an ABB industrial robot with an ABB IRC5 controller. A method to improve motion smoothness and decrease latency using the existing ABB IRC5 robot controller without access to any low-level interface is proposed. Design/methodology/ approach - The proposed control algorithm includes a high-level proportional-integral-derivative controller (PID) controller used to dynamically generate reference velocities for different travel ranges of the tool centre point (TCP) of the robot. Communication with the ABB IRC5 controller was performed utilising the ABB PC software development kit. The multitasking feature of the IRC5 controller was used to enhance the communication frequency between the controller and the remote application. Trajectory tracking experiments of a pre-defined three-dimensional trajectory were carried out and the benefits of the proposed algorithm were demonstrated. The robot was intentionally installed on a wobbly table and its vibrations were recorded using a six-degrees-of-freedom force/torque sensor fitted to the tool mounting interface of the robot. The robot vibrations were used as a measure of the smoothness of the tracking movements. Findings - A communication rate of up to 250 Hz between the computer and the controller was established using C#.Net. Experimental results demonstrating the robot TCP, tracking errors and robot vibrations for different control approaches were provided and analysed. It was demonstrated that the proposed approach results in the smoothest motion with tracking errors of < 0.2 mm. Research limitations/implications - The proposed approach may be employed to produce smooth motion for a remotely operated ABB industrial robot with the existing ABB IRC5 controller. However, to achieve high-bandwidth path following, the inherent latency of the controller must be overcome, for example by utilising a low-level interface. It is particularly useful for applications including a large number of short manipulation segments, which is typical in teleoperation applications. Social implications - Using the proposed technique, off-the-shelf industrial robots can be used for research and industrial applications where remote control is required. Originality/value - Although low-level control interface for industrial robots seems to be the ideal long-term solution for teleoperation applications, the proposed remote control technique allows out-of-the-box ABB industrial robots with IRC5 controllers to achieve high efficiency and manipulation smoothness without requirements of any low-level programming interface. © Copyright - 2014 Emerald Group Publishing Limited. All rights reserved.

Validation of a trunk-mounted accelerometer to measure peak impacts during team sport movements

This study assessed the validity of an accelerometer to measure impacts in team sports. 76 participants completed a team sport circuit. Accelerations were collected concurrently at 100 Hz using an accelerometer and a 36-camera motion analysis system. The largest peak accelerations per movement were compared in 2 ways: i) pooled together and filtered at 13 different cut-off frequencies (range 6-25 Hz) to identify the optimal filtering frequency, and ii) the optimal cut-off frequency split into the 7 movements performed (n=532). Raw and 25-16 Hz filtering frequencies significantly overestimated and 6 Hz underestimated motion analysis peak accelerations (P <0.007). The 12 Hz filtered accelerometer data revealed the strongest relationship with motion analysis data (accuracy - 0.01±0.27 g, effect size - 0.01, agreement - 0.55 to 0.53 g, precision 0.27 g, and relative error 5.5%; P=1.00). The accelerometer underestimated peak accelerations during tackling and jumping, and overestimated during walking, jogging, sprinting and change of direction. Lower agreement and reduced precision were associated with sprinting, jumping and tackling. The accelerometer demonstrated an acceptable level of concurrent validity compared to a motion analysis system when filtered at a cut-off frequency of 12 Hz. The results advocate the use of accelerometers to measure movements in team sport.

Nocebo effects in the treatment of major depression: results from an individual study participant-level meta-analysis of the placebo arm of duloxetine clinical trials

BACKGROUND: The nocebo effect, when a harmless substance creates harmful effects in a person who takes it, is a clinically salient yet seldom studied phenomenon that may be associated with poorer treatment outcomes, perceived adverse events, and treatment discontinuation. The covert presence of nocebo responders in clinical trials may contribute to outcome variance in both placebo and active treatment arms for important primary and secondary endpoints. Nocebo effects are thought to be driven by expectancy and conditioning. METHOD: This study analyzed pooled clinical trial data in the placebo arms of controlled trials of antidepressant medications to investigate variables associated with the emergence of adverse outcomes in placebo-treated participants (N = 2,457). Specifically, we examined treatment-emergent adverse events (TEAEs) and discontinuation in placebo-treated individuals. Trials were commenced between 1993 and 2010 as studies of duloxetine versus active comparator and/or placebo. RESULTS: TEAEs were reported by 1,569 placebo-treated participants (63.9%), with 115 (4.7%) discontinuing from the studies due to TEAEs and 274 (11.2%) showing worsening of Hamilton Depression Rating Scale total score during placebo treatment. There was specifically no evidence to support the expectancy hypothesis, that reported TEAEs were influenced by adverse effects described in the clinical trials participant information and consent forms, or the conditioning hypothesis, that reported TEAEs would be influenced by adverse effect profiles of previous antidepressant medications used by these study participants. There was some evidence to suggest that people who had previously used complementary medications were more likely to report TEAEs. Variables specific to individual studies were the strongest predictors of TEAEs. DISCUSSION: In this study, TEAEs were very common among placebo-treated clinical trial participants. Unexpectedly, there was no evidence to associate TEAEs with adverse clinical outcomes, nor were the conditioning or expectancy hypotheses supported by these data. CONCLUSIONS: The nocebo effect is a common, covert, and poorly understood driver of clinical outcomes that requires further investigation.

Separation of Doppler radar-based respiratory signatures

Respiration detection using microwave Doppler radar has attracted significant interest primarily due to its unobtrusive form of measurement. With less preparation in comparison with attaching physical sensors on the body or wearing special clothing, Doppler radar for respiration detection and monitoring is particularly useful for long-term monitoring applications such as sleep studies (i.e. sleep apnoea, SIDS). However, motion artefacts and interference from multiple sources limit the widespread use and the scope of potential applications of this technique. Utilising the recent advances in independent component analysis (ICA) and multiple antenna configuration schemes, this work investigates the feasibility of decomposing respiratory signatures into each subject from the Doppler-based measurements. Experimental results demonstrated that FastICA is capable of separating two distinct respiratory signatures from two subjects adjacent to each other even in the presence of apnoea. In each test scenario, the separated respiratory patterns correlate closely to the reference respiration strap readings. The effectiveness of FastICA in dealing with the mixed Doppler radar respiration signals confirms its applicability in healthcare applications, especially in long-term home-based monitoring as it usually involves at least two people in the same environment (i.e. two people sleeping next to each other). Further, the use of FastICA to separate involuntary movements such as the arm swing from the respiratory signatures of a single subject was explored in a multiple antenna environment. The separated respiratory signal indeed demonstrated a high correlation with the measurements made by a respiratory strap used currently in clinical settings.

Home range, habitat use and movements by the little raven (Corvus mellori) in a coastal peri-urban landscape

Context In peri-urban environments, high availability of anthropogenic resources may result in relatively high abundances of some species, with potentially negative implications for other native biota. Effective management of such impacts requires understanding of the spatial ecology of problem species. However, home range and habitat use have not been described for the little raven (Corvus mellori), a superabundant native predator that occurs in urban and natural habitats, including those where threatened shorebirds breed. Aims The aim of this study was to provide basic information on little raven home range, habitat use and movements in a coastal peri-urban landscape. Methods Between October 2011 and January 2012 we radio-tracked 20 little ravens captured in a coastal wetland (near Melbourne, Australia). Key results Little ravens were highly mobile, moving up to 9.9km in an hour (median≤2km), and had large ranges: Minimum Convex Polygons were 1664-9989ha (median≤3362ha). Although most birds used both anthropogenic and natural habitats, some birds strongly selected for coastal wetland habitat. Birds used multiple roosts during the study period, most of which occurred in grassland (58.7%) or urban (22.3%) areas. Movement of up to 8.3km (median≤2.2km) between roosts during the night was also detected. Conclusions Ravens were highly mobile and used large home ranges and a variety of habitats, with habitat preferences varying between birds. Implications Considering the large home ranges and inter-individual variation in habitat preferences of little raven populations, localised management to reduce their impacts on breeding shorebirds is unlikely to be successful. Journal compilation

Detection of dynamic background due to swaying movements from motion features

Dynamically changing background (dynamic background) still presents a great challenge to many motion-based video surveillance systems. In the context of event detection, it is a major source of false alarms. There is a strong need from the security industry either to detect and suppress these false alarms, or dampen the effects of background changes, so as to increase the sensitivity to meaningful events of interest. In this paper, we restrict our focus to one of the most common causes of dynamic background changes: 1) that of swaying tree branches and 2) their shadows under windy conditions. Considering the ultimate goal in a video analytics pipeline, we formulate a new dynamic background detection problem as a signal processing alternative to the previously described but unreliable computer vision-based approaches. Within this new framework, we directly reduce the number of false alarms by testing if the detected events are due to characteristic background motions. In addition, we introduce a new data set suitable for the evaluation of dynamic background detection. It consists of real-world events detected by a commercial surveillance system from two static surveillance cameras. The research question we address is whether dynamic background can be detected reliably and efficiently using simple motion features and in the presence of similar but meaningful events, such as loitering. Inspired by the tree aerodynamics theory, we propose a novel method named local variation persistence (LVP), that captures the key characteristics of swaying motions. The method is posed as a convex optimization problem, whose variable is the local variation. We derive a computationally efficient algorithm for solving the optimization problem, the solution of which is then used to form a powerful detection statistic. On our newly collected data set, we demonstrate that the proposed LVP achieves excellent detection results and outperforms the best alternative adapted from existing art in the dynamic background literature.

Prosthetic motor imaginary task classification using single channel of electroencephalography

Brain Computer Interface (BCI) is playing a very important role in human machine communications. Recent communication systems depend on the brain signals for communication. In these systems, users clearly manipulate their brain activity rather than using motor movements in order to generate signals that could be used to give commands and control any communication devices, robots or computers. In this paper, the aim was to estimate the performance of a brain computer interface (BCI) system by detecting the prosthetic motor imaginary tasks by using only a single channel of electroencephalography (EEG). The participant is asked to imagine moving his arm up or down and our system detects the movement based on the participant brain signal. Some features are extracted from the brain signal using Mel-Frequency Cepstrum Coefficient and based on these feature a Hidden Markov model is used to help in knowing if the participant imagined moving up or down. The major advantage in our method is that only one channel is needed to take the decision. Moreover, the method is online which means that it can give the decision as soon as the signal is given to the system. Hundred signals were used for testing, on average 89 % of the up down prosthetic motor imaginary tasks were detected correctly. This method can be used in many different applications such as: moving artificial prosthetic limbs and wheelchairs due to it's high speed and accuracy.

Prosthetic motor imaginary task classification based on EEG quality assessment features

Brain Computer Interface (BCI) plays an important role in the communication between human and machines. This communication is based on the human brain signals. In these systems, users use their brain instead of the limbs or body movements to do tasks. The brain signals are analyzed and translated into commands to control any communication devices, robots or computers. In this paper, the aim was to enhance the performance of a brain computer interface (BCI) systems through better prosthetic motor imaginary tasks classification. The challenging part is to use only a single channel of electroencephalography (EEG). Arm movement imagination is the task of the user, where (s)he was asked to imagine moving his arm up or down. Our system detected the imagination based on the input brain signal. Some EEG quality features were extracted from the brain signal, and the Decision Tree was used to classify the participant's imagination based on the extracted features. Our system is online which means that it can give the decision as soon as the signal is given to the system (takes only 20 ms). Also, only one EEG channel is used for classification which reduces the complexity of the system which leads to fast performance. Hundred signals were used for testing, on average 97.4% of the up-down prosthetic motor imaginary tasks were detected correctly. This method can be used in many different applications such as: moving artificial limbs and wheelchairs due to it's high speed and accuracy.

Metabolic power method underestimates energy expenditure in field sport movements using a GPS tracking system

The purpose of this study was to assess the validity of a GPS tracking system to estimate energy expenditure (EE) during exercise and field sport locomotor movements. Twenty-seven participants each completed one 90 minute exercise session on an outdoor synthetic futsal pitch. During the exercise session participants wore a 5 Hz GPS unit interpolated to 15 Hz (SPI HPU, GPSports Pty Ltd, Australia) and a portable gas analyser (Metamax® 3B, Cortex Pty Ltd, Germany) which acted as the criterion measure of EE. The exercise session was comprised of alternating five minute exercise bouts of randomised walking, jogging, running or a field sport circuit (x3) followed by 10 minutes of recovery. One-way ANOVA showed significant (p<0.01) and very large underestimations between GPS metabolic power derived EE and VO2 derived EE for all field sport circuits (% difference ≈ -44%). No differences in EE were observed for the jog (7.8%) and run (4.8%) while very large overestimations were found for the walk (43.0%). The GPS metabolic power EE over the entire 90 minute session was significantly lower (p<0.01) than the VO2 EE, resulting in a moderate underestimation overall (-19%). The results of this study suggest that a GPS tracking system using the metabolic power model of EE does not accurately estimate EE in field sport movements or over an exercise session consisting of mixed locomotor activities interspersed with recovery periods; however is able to provide a reasonably accurate estimation of EE during continuous jogging and running.