Tele-Supervised FES-Assisted Exercise for Hemiplegic Upper Limb

Stroke survivors often have upper limb (UL) hemiparesis, limiting their ability to perform activities of daily life (ADLs). Intensive, task-oriented exercise therapy (ET) can improve UL function, but motivation to perform sufficient ET is difficult to maintain. Here we report on a trial in which a workstation was deployed in the homes of chronic stroke survivors to enable tele-coaching of ET in the guise of computer games. Participants performed 6 weeks of 1 hour/day, 5 days/week ET. Hand opening and grasp were assisted with functional electrical stimulation (FES). The primary outcome measure was the Action Research Arm Test (ARAT). Secondary outcome measures included a quantitative test of UL function performed on the workstation, grasp force measurements and transcranial magnetic stimulation (TMS). Improvements were seen in the functional tests, but surprisingly, not in the TMS responses. An important finding was that participants commencing with intermediate functional scores improved the most.

CONCLUSIONS: 1) Daily, tele-supervised FES-ET in chronic stroke survivors is feasible with commercially-available technology. 2) The intervention can significantly improve UL function, particularly in people who start with an intermediate level of function. 3) Significant improvements in UL function can occur in the absence of changes in TMS responses.

Understanding perception and action in sport:How can virtual reality technology help?

Although technology can facilitate improvements in performance by allowing us to understand, monitor and evaluate performance, improvements must ultimately come from within the athlete. The first part of this article will focus on understanding how perception and action relate to performance from two different theoretical viewpoints. The first will be predominantly a cognitive or indirect approach that suggests that expertise and decision-making processes are mediated by athletes accruing large knowledge bases that are built up through practice and experience. The second, and alternative approach, will advocate a more 'direct' solution, where the athlete learns to 'tune' into the relevant information that is embedded in their relationship with the surrounding environment and unfolding action. The second part of the article will attempt to show how emerging virtual reality technology is revealing new evidence that helps us understand elite performance. Possibilities of how new types of training could be developed from this technology will also be discussed. © 2014 Crown Copyright.

New methods for studying perception and action coupling

To study perception and action, Gibson advocated that “the laboratory must be like life” (Gibson, 1979, p. 3). In other words, the interactive relationship between an organism and his/her envi- ronment must be maintained so that the behavior observed in an experimental context mirrors, as closely as possible, the behavior observed in a realistic sport setting. The concept of repre- sentative design introduced by Brunswik in 1956 emphasized the need to have experimental tasks that allow the player to pick up perceptual information that specifies a property of the environment-actor system (Araújo et al., 2005; see also Chapter 24). In this chapter we will provide a brief overview of the methodologies used to study perception and action in sport and present, in some detail, the opportunities new methodologies such as immersive, interactive vir- tual reality can offer researchers in sport expertise.

Role of early visual cortex in trans-saccadic memory of object features

Early visual cortex (EVC) participates in visual feature memory and the updating of remembered locations across saccades, but its role in the trans-saccadic integration of object features is unknown. We hypothesized that if EVC is involved in updating object features relative to gaze, feature memory should be disrupted when saccades remap an object representation into a simultaneously perturbed EVC site. To test this, we applied transcranial magnetic stimulation (TMS) over functional magnetic resonance imaging-localized EVC clusters corresponding to the bottom left/right visual quadrants (VQs). During experiments, these VQs were probed psychophysically by briefly presenting a central object (Gabor patch) while subjects fixated gaze to the right or left (and above). After a short memory interval, participants were required to detect the relative change in orientation of a re-presented test object at the same spatial location. Participants either sustained fixation during the memory interval (fixation task) or made a horizontal saccade that either maintained or reversed the VQ of the object (saccade task). Three TMS pulses (coinciding with the pre-, peri-, and postsaccade intervals) were applied to the left or right EVC. This had no effect when (a) fixation was maintained, (b) saccades kept the object in the same VQ, or (c) the EVC quadrant corresponding to the first object was stimulated. However, as predicted, TMS reduced performance when saccades (especially larger saccades) crossed the remembered object location and brought it into the VQ corresponding to the TMS site. This suppression effect was statistically significant for leftward saccades and followed a weaker trend for rightward saccades. These causal results are consistent with the idea that EVC is involved in the gaze-centered updating of object features for trans-saccadic memory and perception.

“Paths for Action”: Leadership Theory and Practice in Complex Public Sector Systems

The nature and challenges of public sector leadership and management are examined in four case studies of project management in complex metropolitan environments. The cases selected by the authors as representative of contextual factors affecting decision-making processes and project outcomes. Drawing on recent theoretical work on complex leadership approaches (Uhl-Bein et al 2007, Hazy 2008, Lichtenstein & Plowman 2009), the authors assess leadership practices enacted and the circumstances that influence these practices. Leadership types theorized by Uhl-Bein et al (2007) are identified operating at different levels and across networks, with contextual factors outlined. The article concludes with a framework for leadership practice and management identifying network facilitation and complexity friendly tools as a practice within complex public sector systems.

Engaging the Senses: Object-based learning in higher education

The use of museum collections as a path to learning for university students is fast becoming a new pedagogy for higher education. Despite a strong tradition of using lectures as a way of delivering the curriculum, the positive benefits of ‘active’ and ‘experiential learning’ are being recognised in universities at both a strategic level and in daily teaching practice. As museum artefacts, specimens and art works are used to evoke, provoke, and challenge students’ engagement with their subject, so transformational learning can take place. This unique book presents the first comprehensive exploration of ‘object-based learning’ as a pedagogy for higher education in a broad context. An international group of authors offer a spectrum of approaches at work in higher education today. They explore contemporary principles and practice of object-based learning in higher education, demonstrating the value of using collections in this context and considering the relationship between academic discipline and object-based learning as a teaching strategy.

Young Stellar Object VARiability (YSOVAR): Long Timescale Variations in the Mid-infrared

The YSOVAR (Young Stellar Object VARiability) Spitzer Space Telescope observing program obtained the first extensive mid-infrared (3.6 and 4.5 μm) time series photometry of the Orion Nebula Cluster plus smaller footprints in 11 other star-forming cores (AFGL 490, NGC 1333, Mon R2, GGD 12-15, NGC 2264, L1688, Serpens Main, Serpens South, IRAS 20050+2720, IC 1396A, and Ceph C). There are ~29,000 unique objects with light curves in either or both IRAC channels in the YSOVAR data set. We present the data collection and reduction for the Spitzer and ancillary data, and define the "standard sample" on which we calculate statistics, consisting of fast cadence data, with epochs roughly twice per day for ~40 days. We also define a "standard sample of members" consisting of all the IR-selected members and X-ray-selected members. We characterize the standard sample in terms of other properties, such as spectral energy distribution shape. We use three mechanisms to identify variables in the fast cadence data—the Stetson index, a χ2 fit to a flat light curve, and significant periodicity. We also identified variables on the longest timescales possible of six to seven years by comparing measurements taken early in the Spitzer mission with the mean from our YSOVAR campaign. The fraction of members in each cluster that are variable on these longest timescales is a function of the ratio of Class I/total members in each cluster, such that clusters with a higher fraction of Class I objects also have a higher fraction of long-term variables. For objects with a YSOVAR-determined period and a [3.6]-[8] color, we find that a star with a longer period is more likely than those with shorter periods to have an IR excess. We do not find any evidence for variability that causes [3.6]-[4.5] excesses to appear or vanish within our data set; out of members and field objects combined, at most 0.02% may have transient IR excesses.

Kinect and Episodic Reasoning for Human Action Recognition

This paper presents a method for rational behaviour recognition that combines vision-based pose estimation with knowledge modeling and reasoning. The proposed method consists of two stages. First, RGB-D images are used in the estimation of the body postures. Then, estimated actions are evaluated to verify that they make sense. This method requires rational behaviour to be exhibited. To comply with this requirement, this work proposes a rational RGB-D dataset with two types of sequences, some for training and some for testing. Preliminary results show the addition of knowledge modeling and reasoning leads to a significant increase of recognition accuracy when compared to a system based only on computer vision.