Watch and Learn: Athletes Can Improve by Observing the Actions of Others

Copyright © 2022 Bruton and Wright. Athletes spend a lot of time and effort practicing skills to get better at their sports. In addition to physical practice, athletes can use a technique called action observation to help themselves improve. Action observation is the process of watching movement. Humans naturally learn how to perform movements by watching the movements of other people. For example, from an early age, children learn important skills such as walking, throwing, and kicking by seeing other people perform those actions. Research has shown that watching movements activates similar parts of the brain to those that are involved in performing movement. This means watching sports performance might help athletes improve by strengthening the brain areas used when actions are performed. Coaches and sport psychologists use action observation methods, such as live demonstrations and video footage, to help athletes improve their techniques, develop their confidence, and get better at their sports

Right-lateralized alpha desynchronization during regularity discrimination: Hemispheric specialization or directed spatial attention?

When actively classifying abstract patterns according to their regularity, alpha desynchronization (ERD) becomes right lateralized over posterior brain areas. This could reflect temporary enhancement of contralateral visual inputs and specifically a shift of attention to the left, or right hemisphere specialization for regularity discrimination. This study tested these competing hypotheses. Twenty-four participants discriminated between dot patterns containing a reflection or a translation. The direction of the transformation, which matched one half onto the other half, was either vertical or horizontal. The strategy of shifting attention to one side of the patterns would not produce lateralized ERD in the horizontal condition. However, right-lateralized ERD was found in all conditions, regardless of orientation. We conclude that right hemisphere networks that incorporate the early posterior regions are specialized for regularity discrimination

Reducing Grip Uncertainty During Initial Prosthetic Hand Use Improves Eye-Hand Coordination and Lowers Mental Workload

The reliance on vision to control a myoelectric prosthesis is cognitively burdensome and contributes to device abandonment. The feeling of uncertainty when gripping an object is thought to be the cause of this overreliance on vision in hand-related actions. We explored if experimentally reducing grip uncertainty alters the visuomotor control and mental workload experienced during initial prosthesis use. In a repeated measures design, twenty-one able-bodied participants took part in a pouring task across three conditions: (a) using their anatomical hand, (b) using a myoelectric prosthetic hand simulator, and (c) using a myoelectric prosthetic hand simulator with Velcro attached to reduce grip uncertainty. Performance, gaze behaviour (using mobile eye-tracking) and self-reported mental workload, was measured. Results showed that using a prosthesis (with or without Velcro) slowed task performance, impaired typical eye-hand coordination and increased mental workload compared to anatomic hand control. However, when using the prosthesis with Velcro, participants displayed better prosthesis control, more effective eye-hand coordination and reduced mental workload compared to when using the prosthesis without Velcro. These positive results indicate that reducing grip uncertainty could be a useful tool for encouraging more effective prosthesis control strategies in the early stages of prosthetic hand learning

Remarkable Progress with Small-Molecule Modulation of TRPC1/4/5 Channels: Implications for Understanding the Channels in Health and Disease

Proteins of the TRPC family can form many homo- and heterotetrameric cation channels permeable to Na+, K+ and Ca2+. In this review, we focus on channels formed by the isoforms TRPC1, TRPC4 and TRPC5. We review evidence for the formation of different TRPC1/4/5 tetramers, give an overview of recently developed small-molecule TRPC1/4/5 activators and inhibitors, highlight examples of biological roles of TRPC1/4/5 channels in different tissues and pathologies, and discuss how high-quality chemical probes of TRPC1/4/5 modulators can be used to understand the involvement of TRPC1/4/5 channels in physiological and pathophysiological processes

Measuring patient-perceived quality of care in US hospitals using Twitter

BACKGROUND: Patients routinely use Twitter to share feedback about their experience receiving healthcare. Identifying and analysing the content of posts sent to hospitals may provide a novel real-time measure of quality, supplementing traditional, survey-based approaches. OBJECTIVE: To assess the use of Twitter as a supplemental data stream for measuring patient-perceived quality of care in US hospitals and compare patient sentiments about hospitals with established quality measures. DESIGN: 404 065 tweets directed to 2349 US hospitals over a 1-year period were classified as having to do with patient experience using a machine learning approach. Sentiment was calculated for these tweets using natural language processing. 11 602 tweets were manually categorised into patient experience topics. Finally, hospitals with ≥50 patient experience tweets were surveyed to understand how they use Twitter to interact with patients. KEY RESULTS: Roughly half of the hospitals in the US have a presence on Twitter. Of the tweets directed toward these hospitals, 34 725 (9.4%) were related to patient experience and covered diverse topics. Analyses limited to hospitals with ≥50 patient experience tweets revealed that they were more active on Twitter, more likely to be below the national median of Medicare patients (p<0.001) and above the national median for nurse/patient ratio (p=0.006), and to be a non-profit hospital (p<0.001). After adjusting for hospital characteristics, we found that Twitter sentiment was not associated with Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) ratings (but having a Twitter account was), although there was a weak association with 30-day hospital readmission rates (p=0.003). CONCLUSIONS: Tweets describing patient experiences in hospitals cover a wide range of patient care aspects and can be identified using automated approaches. These tweets represent a potentially untapped indicator of quality and may be valuable to patients, researchers, policy makers and hospital administrators

Statistical comparison of InSAR tropospheric correction techniques

Correcting for tropospheric delays is one of the largest challenges facing the interferometric synthetic aperture radar (InSAR) community. Spatial and temporal variations in temperature, pressure, and relative humidity create tropospheric signals in InSAR data, masking smaller surface displacements due to tectonic or volcanic deformation. Correction methods using weather model data, GNSS and/or spectrometer data have been applied in the past, but are often limited by the spatial and temporal resolution of the auxiliary data. Alternatively a correction can be estimated from the interferometric phase by assuming a linear or a power-law relationship between the phase and topography. Typically the challenge lies in separating deformation from tropospheric phase signals. In this study we performed a statistical comparison of the state-of-the-art tropospheric corrections estimated from the MERIS and MODIS spectrometers, a low and high spatial-resolution weather model (ERA-I and WRF), and both the conventional linear and new power-law empirical methods. Our test-regions include Southern Mexico, Italy, and El Hierro. We find spectrometers give the largest reduction in tropospheric signal, but are limited to cloud-free and daylight acquisitions. We find a ~ 10–20% RMSE increase with increasing cloud cover consistent across methods. None of the other tropospheric correction methods consistently reduced tropospheric signals over different regions and times. We have released a new software package called TRAIN (Toolbox for Reducing Atmospheric InSAR Noise), which includes all these state-of-the-art correction methods. We recommend future developments should aim towards combining the different correction methods in an optimal manner

Novel Environmental Features for Robust Multisensor Navigation

Many navigation techniques have now become so reliant on GNSS that there is no back up when there is limited or no signal reception. If there is interference, intentional or otherwise, with the signal, navigation could be lost or become misleading [1]. Other navigation techniques harness different technologies such as Wi-Fi [2], eLoran and inertial navigation. However, each of these techniques has its own limitations, such as coverage, degradation in urban areas or solution drift [3]. Therefore there is a need for new navigation and positioning techniques that may be integrated with GNSS to increase the reliability of the system as a whole. This paper presents the results of a feasibility study to identify a set of novel environmental features that could be used for navigation in the temporary absence of GNSS or degradation of the signal. By measuring these features during times of GNSS availability a map can be produced. This can be referred to during times of limited reception, a principle already used for some Wi-Fi positioning techniques [2]. Therefore a “measurable” can be defined as a feature either man-made or natural that is spatially distinct and has limited temporal variation. Possibilities considered include magnetic anomalies [4], light intensity and road signs. Firstly, a brainstorming exercise and a literature study were conducted to generate a list of possible environmental features that was assessed for the viability of each candidate. The features were ranked according to three criteria: practicality, precision and coverage. The definition of practicality for each measurable was that a suitable detector must be installable on a road vehicle, particularly an emergency vehicle, at a reasonable cost with minimal alterations to the vehicle. Precision was defined in terms of the spatial variation of the environmental feature and thus the accuracy with which position information might be derived from it. Coverage was assessed in terms of the availability of the feature over a range of different environments. Continuous coverage is not required because the new measurables may be used in combination and integrated with dead reckoning techniques, such as odometry and inertial navigation [3]. The outcome of the viability study was used to determine which features are to be experimentally tested. Magnetic anomalies, road texture and a dozen other environmental features were found to be worth investigation. Features which were discounted include wind speed and pulsars [5]. The initial experiment was carried out on foot in Central London. The same tests were repeated on two separate days, with a closed loop circuit walked three times on each occasion. This experiment used an Inertial Measurement Unit (IMU), comprising accelerometer and gyro triads, together with a barometer, three-axis magnetometer and GNSS receiver. The experiment was also recorded using a camcorder from the point of view of a pedestrian, enabling visual and audio features of the environment to be assessed. Magnetic anomalies were found to be a promising source of position information. Peaks in the magnetometer data were observed on all rounds at approximately the same positions. There were also similarities seen in the temperature profiles after correcting for the temporal variation of the background temperature. Another potential source of position information was found to be text-based signs. It is relatively simple to extract text from camera images and it is easily stored in a feature database. However, methods of dealing with identically-worded signs in close proximity will need to be developed. Sound levels were analysed in 10s intervals for the mean, minimum and maximum sound volume. There was no clear correlation observed between the different rounds of the experiment. Due to the pedestrian experimental results sound levels of the surroundings will not be used in further experimentation. An alternative area of enquiry for using sound (in the vehicular experiments) is using microphones to indirectly measure road texture based on the noise from the wheel contact with the road [6]. The paper will also present results of road vehicle experiments. Multiple circuits of the same routes will be compared. Different environments will be assessed including rural, dual carriageways, suburban and urban roads. Sensors to be used include the IMU and 3-axis magnetometer from the pedestrian experiment, a barometer, gas sensors, a microphone, an axle-mounted accelerometer, an ambient light sensor and a thermometer. These will be placed either on, inside or under the vehicle as determined by the individual needs of the sensors. The results will be used to determine which of these sensors could be potentially used for a multisensor integrated navigation system and also the environments in which they work optimally. Using the results of the three feasibility study phases (literature review, pedestrian and road experiment) the next project stage will be to produce a demonstration system that uses the most feasible features of the environment and creates a map database during times GNSS is present. This database will then be used for navigation in times of need. In the long term, it is envisaged that this technique will be implemented cooperatively, with a batch of vehicles collecting feature data and contributing it to a common shared database. / References [1] Thomas, M., et al., Global Navigation Space Systems: Reliance and Vulnerabilities, London, UK: Royal Academy of Engineering, 2011. [2] Jones, K., L. Liu, and F. Alizadeh-Shabdiz, “Improving Wireless Positioning with Look-ahead Map-Matching,” Proc. MobiQuitous 2007, Phildaelphia, PA, February 2008, pp. 1-8. [3] Groves, P.D., Principles of GNSS, Inertial, and Multisensor Intergrated Navigation Systems, Second Edition, Artech House, 2013. [4] Judd, T., and T. Vu, “Use of a New Pedometric Dead Reckoning Module in GPS Denied Environments,” Proc. IEEE/ION PLANS, Monterey, CA, May 2008, pp. 120?128. [5] Walter, D. J., "Feasibility study of novel environmental feature mapping to bridge GNSS outage," Young Navigator Conference, London, 2012. [6] Mircea, M., et al., “Strategic mapping of the ambient noise produced by road traffic, accordingly to European regulations,” Proc. IEEE International Conference on Automation, Quality and Testing, Robotics, Cluj Napoca, Romania, May 2008

Recommendations for Combining Action Observation and Motor Imagery Interventions in Sport

Combined action observation and motor imagery (AOMI) interventions involve observing a movement demonstration, usually via video, whilst at the same time imagining the feelings and sensations involved in executing the observed action. Research findings indicate that AOMI interventions can be effective for improving sport performance, yet no guidelines currently exist within the literature to inform applied sport psychologists how to develop and implement AOMI interventions with athletes. The aim of this article is to address this gap in the applied sport psychology literature. Accordingly, the article provides an overview of the ‘Science of AOMI’ by discussing the neurophysiological, cognitive, psychological and performance effects of AOMI interventions to introduce the concept of AOMI and potential benefits of AOMI interventions in sport. The article then covers the ‘Practice of AOMI’ by discussing practical recommendations for applied sport psychologists on how to develop and implement AOMI interventions for performance enhancement purposes. Important considerations related to filming the action observation video are discussed, such as selection of the model and choice of visual perspective. Guidelines are then provided for developing and delivering personalized kinesthetic imagery instructions for use by the athlete in synchrony with action observation

Recommendations for Combining Action Observation and Motor Imagery Interventions in Sport

Copyright © 2021 the author(s). Combined action observation and motor imagery (AOMI) interventions involve observing a movement demonstration, usually via video, whilst at the same time imagining the feelings and sensations involved in executing the observed action. Research findings indicate that AOMI interventions can be effective for improving sport performance, yet no guidelines currently exist within the literature to inform applied sport psychologists how to develop and implement AOMI interventions with athletes. The aim of this article is to address this gap in the applied sport psychology literature. Accordingly, the article provides an overview of the ‘Science of AOMI’ by discussing the neurophysiological, cognitive, psychological and performance effects of AOMI interventions to introduce the concept of AOMI and potential benefits of AOMI interventions in sport. The article then covers the ‘Practice of AOMI’ by discussing practical recommendations for applied sport psychologists on how to develop and implement AOMI interventions for performance enhancement purposes. Important considerations related to filming the action observation video are discussed, such as selection of the model and choice of visual perspective. Guidelines are then provided for developing and delivering personalized kinesthetic imagery instructions for use by the athlete in synchrony with action observation