arXiv subjects

Michael S. Crouch

Publications and source records attributed to Michael S. Crouch.

3 recordsLinked to original sources

arXiv2021

Natural Typing Recognition via Surface Electromyography

By using a computer keyboard as a finger recording device, we construct the largest existing dataset for gesture recognition via surface electromyography (sEMG), and use deep learning to achieve over 90% character-level accuracy on reconstructing typed text entirely from measured muscle potentials. We prioritize the temporal structure of the EMG signal instead of the spatial structure of the electrode layout, using network architectures inspired by those used for real-time spoken language transcription. Our architecture recognizes the rapid movements of natural computer typing, which occur at irregular intervals and often overlap in time. The extensive size of our dataset also allows us to study gesture recognition after synthetically downgrading the spatial or temporal resolution, showing the system capabilities necessary for real-time gesture recognition.

cs.HC↗

arXiv2021

Surface Electromyography as a Natural Human-Machine Interface: A Review

Surface electromyography (sEMG) is a non-invasive method of measuring neuromuscular potentials generated when the brain instructs the body to perform both fine and coarse locomotion. This technique has seen extensive investigation over the last two decades, with significant advances in both the hardware and signal processing methods used to collect and analyze sEMG signals. While early work focused mainly on medical applications, there has been growing interest in utilizing sEMG as a sensing modality to enable next-generation, high-bandwidth, and natural human-machine interfaces. In the first part of this review, we briefly overview the human skeletomuscular physiology that gives rise to sEMG signals followed by a review of developments in sEMG acquisition hardware. Special attention is paid towards the fidelity of these devices as well as form factor, as recent advances have pushed the limits of user comfort and high-bandwidth acquisition. In the second half of the article, we explore work quantifying the information content of natural human gestures and then review the various signal processing and machine learning methods developed to extract information in sEMG signals. Finally, we discuss the future outlook in this field, highlighting the key gaps in current methods to enable seamless natural interactions between humans and machines.

cs.HC↗

arXiv2003

The Morphological Butcher-Oemler effect in the SDSS Cut&Enhance Galaxy Cluster Catalog

We investigate the evolution of the fractions of late type cluster galaxies as a function of redshift, using one of the largest, most uniform cluster samples available. The sample consists of 514 clusters of galaxies in the range 0.02<z<0.3 from the Sloan Digital Sky Survey Cut & Enhance galaxy cluster catalog. This catalog was created using a single automated cluster finding algorithm on uniform data from a single telescope, with accurate CCD photometry, thus, minimizing selection biases. We use four independent methods to analyze the evolution of the late type galaxy fraction. Specifically, we select late type galaxies based on: restframe g-r color, u-r color, galaxy profile fitting and concentration index. The first criterion corresponds to the one used in the classical Butcher-Oemler analyses. The last three criteria are more sensitive to the morphological type of the galaxies. In all four cases, we find an increase in the fraction of late type galaxies with increasing redshift, significant at the 99.9% level. The results confirm that cluster galaxies do change colors with redshift (the Butcher-Oemler effect) and, in addition, they change their morphology to later-type toward higher redshift -- indicating a morphological equivalent of the Butcher-Oemler effect. We also find a tendency of richer clusters to have lower fractions of late type galaxies. The trend is consistent with a ram pressure stripping model, where richer clusters have more effective ram pressure due to their higher temperature.

astro-ph↗