Words Per Minute Research Articles

High performance P300 spellers using GPT2 word prediction with cross-subject training

ABSTRACT Amyotrophic lateral sclerosis (ALS) severely impairs patients’ ability to communicate, often leading to a decline in their quality of life within a few years of diagnosis. The P300 speller brain–computer interface (BCI) offers an alternative communication method by interpreting a subject’s EEG response to flashing characters presented on a grid interface. This paper addresses the common speed limitations encountered in training efficient P300-based multi-subject classifiers by introducing innovative ‘across-subject’ classifiers. We leverage a combination of the second-generation Generative Pre-Trained Transformer (GPT2) and Dijkstra’s algorithm to optimize stimuli and suggest word completion choices based on subjects’ typing history. Additionally, we employ a multi-layered smoothing technique to accommodate out-of-vocabulary (OOV) words. Through extensive simulations employing random sampling of EEG data from multiple subjects, we demonstrate significant speed enhancements in typing passages containing rare and OOV words. These optimizations result in approximately 10 % improvement in character-level typing speed and up to 40 % improvement in multi-word prediction. We demonstrate that augmenting standard row/column highlighting techniques with layered word prediction yields close-to-optimal performance. Furthermore, we explore both ‘within-subject’ and ‘across-subject’ training techniques, showing that speed improvements are consistent across both approaches.

RingGesture: A Ring-Based Mid-Air Gesture Typing System Powered by a Deep-Learning Word Prediction Framework.

Text entry is a critical capability for any modern computing experience, with lightweight augmented reality (AR) glasses being no exception. Designed for all-day wearability, a limitation of lightweight AR glass is the restriction to the inclusion of multiple cameras for extensive field of view in hand tracking. This constraint underscores the need for an additional input device. We propose a system to address this gap: a ring-based mid-air gesture typing technique, RingGesture, utilizing electrodes to mark the start and end of gesture trajectories and inertial measurement units (IMU) sensors for hand tracking. This method offers an intuitive experience similar to raycast-based mid-air gesture typing found in VR headsets, allowing for a seamless translation of hand movements into cursor navigation. To enhance both accuracy and input speed, we propose a novel deep-learning word prediction framework, Score Fusion, comprised of three key components: a) a word-gesture decoding model, b) a spatial spelling correction model, and c) a lightweight contextual language model. In contrast, this framework fuses the scores from the three models to predict the most likely words with higher precision. We conduct comparative and longitudinal studies to demonstrate two key findings: firstly, the overall effectiveness of RingGesture, which achieves an average text entry speed of 27.3 words per minute (WPM) and a peak performance of 47.9 WPM. Secondly, we highlight the superior performance of the Score Fusion framework, which offers a 28.2% improvement in uncorrected Character Error Rate over a conventional word prediction framework, Naive Correction, leading to a 55.2% improvement in text entry speed for RingGesture. Additionally, RingGesture received a System Usability Score of 83 signifying its excellent usability.

Using large language models to accelerate communication for eye gaze typing users with ALS

Accelerating text input in augmentative and alternative communication (AAC) is a long-standing area of research with bearings on the quality of life in individuals with profound motor impairments. Recent advances in large language models (LLMs) pose opportunities for re-thinking strategies for enhanced text entry in AAC. In this paper, we present SpeakFaster, consisting of an LLM-powered user interface for text entry in a highly-abbreviated form, saving 57% more motor actions than traditional predictive keyboards in offline simulation. A pilot study on a mobile device with 19 non-AAC participants demonstrated motor savings in line with simulation and relatively small changes in typing speed. Lab and field testing on two eye-gaze AAC users with amyotrophic lateral sclerosis demonstrated text-entry rates 29–60% above baselines, due to significant saving of expensive keystrokes based on LLM predictions. These findings form a foundation for further exploration of LLM-assisted text entry in AAC and other user interfaces.

Pre-Service Teachers' Writing Accuracy and Fluency: The Role of Weekly Reading

The benefits of Extensive Reading (ER) have been extensively explored in the field of English as a Foreign Language (EFL), particularly in how this approach enhances writing skills. In Ecuador, writing represents one of the biggest challenges students face when acquiring language proficiency. Therefore, this study investigates the effects of weekly story reading (WSR) over an eight-week period on improving written accuracy and fluency among twenty-two EFL pre-service teachers at the Faculty of Education, Quevedo State Technical University, Ecuador. This action research employed a pre/post-test design to collect data before and after the pedagogical intervention. Written book reports were used as the pre- and post-test instruments to identify accuracy issues and measure words-per-minute (WPM) rates. The participants´ tokens of accuracy problems and WPM were quantitatively analyzed through descriptive and inferential statistics. The results showed, among the eight types of writing accuracy analyzed, the three most common errors made by students were punctuation, spelling, and syntax. Notably, they increased as more words were produced in writing. The findings indicate that weekly story reading assignments significantly improved writing fluency, with a mean difference of (M=5.24), and moderately reduced written accuracy problems. Extensive reading might magnify writing skills development among pre-service teachers in Ecuador or other contexts.

Effect of Mechanical Keyboard Switch and Backlight Status on Typing Performance and User Experience

Mechanical keyboards are one of the most used keyboards in daily work, and as the core component of a mechanical keyboard, keyswitches’ characteristics have been widely researched during the last several decades. Meanwhile, keyboards’ backlight design has become an emerging market trend, even though its actual influence on user experience remains unknown. Our study investigated the influence of keyboard switch characteristics and backlight states on typing performance and subjective typing experience. Thirty-three participants were involved in an English-language typing task on keyboards with four typical switches (red, black, brown, and blue types). Software was used to automatically record typing speed and accuracy, and a 7-point Likert subjective scale was used to evaluate typing experience. Results showed that tactile characteristics performed better than linear switches in typing speed, accuracy, and subjective refresh feeling in pair comparison of blue and red switches, and turning on the backlight effect improved typing speed, refreshing feeling, and pleasure. Among six physical characteristics of switches measured in the experiment, pre travel, reset travel, make force, and bottom force contributed more to better typing performance and subjective experience. Our findings provide keyboard manufacturers and researchers with a reference to optimize users’ typing experience.

High-resolution Observations of Clustered Dynamic Extreme-Ultraviolet Bright Tadpoles near the Footpoints of Corona Loops

Abstract An extreme ultraviolet (EUV) close-up view of the Sun offers unprecedented detail of heating events in the solar corona. Enhanced temporal and spatial images obtained by the Solar Orbiter during its first science perihelion enabled us to identify clustered EUV bright tadpoles (CEBTs) occurring near the footpoints of coronal loops. Combining SDO/AIA observations, we determine the altitudes of six distinct CEBTs by stereoscopy, ranging from ~1300 to 3300 km. We then notice a substantial presence of dark, cooler filamentary structures seemingly beneath the CEBTs, displaying periodic up-and-down motions lasting 3 to 5 minutes. This periodic behavior suggests an association of the majority of CEBTs with Type I spicules. Out of the ten selected CEBTs with fast downward velocity, six exhibit corrected velocities close to or exceeding 50 km s-1. These velocities notably surpass the typical speeds of Type I spicules. We explore the generation of such velocities. It indicates that due to the previous limited observations of spicules in the EUV wavelengths, they may reveal novel observational features beyond our current understanding. Gaining insights into these features contributes to a better comprehension of small-scale coronal heating dynamics.

Comparing typing methods for uppercase input in virtual reality: Modifier Key vs. alternative approaches

Typing tasks are basic interactions in a virtual environment (VE). The presence of uppercase letters affects the meanings of words and their readability. By typing uppercase letters on a QWERTY keyboard, the layers can be switched using a modifier key. Considering that VE controllers are typically used in a VE, this input method can result in user fatigue and errors. Thus, this study proposed new alternative interactions for the modifier key input and compared their typing performance and user experience. In an experiment, 30 participants were instructed to type 10 sentences using different typing interaction methods (shift, long press, and double-tap) on a virtual keyboard in a VE. The typing speed, error rate, and number of backspace inputs were measured to compare typing performance. Upon the completion of the typing task, the usability, workload, and sickness associated with each typing method were evaluated. The results showed that the double-tap method exhibited significantly higher typing speed, error rate, ease of use, satisfaction, and workload. This result is consistent with those of previous studies demonstrating that selection tasks were more efficient with fewer hand movements. Thus, this study implies that the double-tap method can be considered as a potential typing interaction for the VEs instead of the traditional method using the shift as a modifier key. Therefore, this study is expected to contribute to the design and development of user-friendly interactions.

The Difference in Achilles Tendon Loading within Immobilizing Boots Based on Ankle Angle, Boot Type, and Walking Speed.

Achilles tendon rupture is an increasingly common injury treated with progressive rehabilitation in an immobilizing boot. However, it is poorly understood how ankle angle, boot type, and walking speed affect Achilles tendon loading. These different parameters would affect Achilles tendon loading in terms of (from greatest to least) ankle angle constraint, immobilization style, boot construction, and walking speed. Descriptive laboratory study. Ten healthy young adults (8 women and 2 men; age, 21 ± 2 years; body mass index, 21.5 ± 3.0 kg/m2) walked in 3 different immobilizing boots at self-selected slow, medium, and fast walking speeds. The authors estimated Achilles tendon loading using a 3-part instrumented insole within the immobilizing boot. The authors averaged tendon load across every stride for each condition and calculated 2-sided bootstrap confidence intervals. Peak tendon loading was compared across all boots, ankle angles, and walking speeds. All boots and immobilization styles decreased tendon loading with respect to shod walking. Immobilization angle had the largest effect on tendon loading, followed by boot construction, and finally walking speed. Ankle angle, boot type, and walking speed can be modified to change loading progression during rehabilitation. Understanding how immobilization affects tendon loading will enable clinicians to modify rehabilitation to improve functional outcomes.

A real-time eye movement-based computer interface for people with disabilities

It is costly to develop systems that enable individuals exposed to Amyotrophic Lateral Sclerosis and similar diseases that directly affect the neuromotor ability to communicate with the outside world. In this study, a budget friendly, high-accuracy, software-based, gaze-controlled, real-time virtual keyboard approach that can enable these people to communicate effectively is proposed. The proposed application requires only a computer and a webcam and has a user-friendly interface that meets the basic daily needs of individuals with disabilities. Since the proposed system does not require an extra action such as blinking, it makes it possible to use computers in advanced stage patients who cannot blink their eyes. The application which uses a deep learning-based facial landmark detector, determines the letters the user focuses on the screen and converts thoughts into text. The part of the screen that the user focuses on is determined with a new selection approach inspired by the K-Nearest Neighbors algorithm. This approach, which does not require blinking, offers high speed and accuracy. In the tests, a typing speed of 23.33 characters per minute is achieved with an accuracy rate of 95.12%. It is anticipated that the study will increase computer accessibility for disabled individuals with limited mobility and contribute to the development of real-time eye tracking systems.

Comparison of mental fatigue using EEG signals and task performance in normal and slump posture adults during computer typing

ObjectivesSlump sitting at workstations has been focused on by clinicians and researchers nowadays; however, there is limited evidence to date that improper positioning affects the mental state. Accordingly, the main objective of this research was to examine the impact of slump posture on mental fatigue and task performance. MethodsA sample of 60 participants, 30 in each group including those with normal and slump postures were recruited to perform an hour of typing on the computer. Mental fatigue through EEG and task performances were considered as outcome measures and then were analyzed statistically in the first and last 3 min of typing. ResultsThe EEG showed a significant increasing trend in theta rhythm at different brain regions during 60 min of typing (P < 0.05). Besides, an interaction between time and posture was observed; it can mean the increasing trend of theta rhythm is different in normal and slump posture acquired sets (P < 0.05).Interestingly the speed of typing was found to be better (P < 0.05) in the normal posture group while no difference found between the groups in terms of errors (P > 0.05). ConclusionOur results showed poor posture can induce more mental fatigue during the given task, than the normal posture. These findings have provided evidence to indicate that in addition to the peripheral and biomechanical component, the assessment of the cortex as the central component should be considered in poor posture individuals. Besides, for any possible physical therapy rehabilitation protocol for the management of poor posture, the peripheral and central components should be focused. Trial registrationRegistered on the Iranian Registry of Clinical Trials on September 21, 2022, IRCT Identifier: IRCT20161026030516N2.

Impact of Atmospheric Turbulence on Dynamic Wind Loads on Heliostats

This study analyses the turbulent wind properties in the lower 10 m of the atmospheric surface layer close to the ground where heliostats are located. Power spectral densities of streamwise and vertical components of wind are analysed, and the frequencies associated with the peak of the spectra are determined using field data collected at two open-country terrains in addition to spectral models of ESDU85020. Variations of the peak frequencies with height from the ground, terrain type and average wind speed are discussed and the impact on heliostat wind loads are described. It is found that while the peak frequency of the streamwise turbulence is between 0.01–0.1 Hz, the peak of the vertical turbulence occurs at frequencies in the range of 0.1–1 Hz. It is shown that smaller heliostats that are located closer to the ground are exposed to turbulent wind fluctuations at a higher frequency and are thus expected to experience wind loads with a higher dominant frequency compared to larger heliostats located higher above the ground. These frequencies need to be considered in design of heliostat drives and structural components

TYPING SPEED TEST: INNOVATION IN TYPING SPEED MEASUREMENT FOR OFFICE MANAGEMENT STUDENTS IN THE INDEPENDENT CURRICULUM

This study aims to develop and evaluate an artificial intelligence (AI)-based typing speed test platform for Office Management program students in the Merdeka Curriculum. In the ever-evolving digital era, fast and accurate typing skills are becoming increasingly important both in the workplace and in education. This study follows the Research &amp; Development method with five main steps: initial research, product development, expert validation, small-scale and large-scale trials. The developed platform, called the Typing Speed ​​Test, is designed to provide real-time feedback, performance analysis, and personalized exercises based on user abilities. The trial involved 150 students from various schools in East Java, showing positive results with 90% of students reporting significant improvements in their typing skills. The platform is considered effective in improving typing speed and accuracy and supports the principles of the Merdeka Curriculum which emphasizes independent learning and the development of 21st-century competencies. The integration of AI into the platform allows for dynamic adaptation of learning, making it a modern solution that can be easily integrated into the educational curriculum. The findings of this study emphasize the importance of digital literacy and the potential of AI in providing innovative and effective learning experiences to prepare students for the demands of an increasingly technology-dependent workforce

Exploring the impact of word prediction assistive features on smartphone keyboards for blind users

Assistive technologies have been developed to enhance blind users’ typing performance, focusing on speed, accuracy, and effort reduction. One such technology is word prediction software, designed to minimize keystrokes required for text input. This study investigates the impact of word prediction on typing performance among blind users using an on-screen QWERTY keyboard. We conducted a comparative study involving eleven blind participants, evaluating both standard QWERTY input and word prediction-assisted typing. Our findings reveal that while word prediction slightly improves typing speed, it does not enhance typing accuracy and increases both physical and temporal workload compared to the default keyboard. We conclude with recommendations for improving word prediction systems, including more efficient editing methods and the integration of voice pitch variations to aid error recognition.

Experimental design for a sustainable society among motorcyclists: The influence of road types and speeds on whole-body vibration exposure and musculoskeletal disorders in motorcyclists

Motorcycles are very popular motorized vehicles and are widely used around the world. The main ergonomic hazard associated with the continuous use of motorcycles is the motorcyclist’s exposure to vibrations, which can potentially cause musculoskeletal disorders (MSDs). This can lead to significant health issues and may also heighten the risk of accidents due to increased driving discomfort. This study aims to investigate the impact of road type and motorcycle speed on WBV exposure and MSD complaints among motorcyclists. An experimental design method was used in this study, with samples subjected to a combination of treatments: riding a motorcycle on different road types and at different speeds. Vibration measurements and calculations were carried out using an accelerometer sensor based on ISO 2631-1, and MSD complaints were assessed using the Body Map Questionnaire (BMQ). The results of this study showed that riding on concrete roads resulted in a significantly higher vibration acceleration of 37.74% and a higher score of MSD complaints of 18.67% compared to asphalt roads. Riding at a speed of 50 km/h resulted in a significantly higher vibration acceleration of 31.03% and a higher score of MSD complaints of 9.49% compared to a speed of 30 km/h. This indicates that increased vibration exposure increased the risk of MSD complaints in this study. These findings highlight the need for measures to mitigate WBV exposure and its adverse health effects on motorcyclists, particularly when riding on rough road surfaces at higher speeds. Recommendations include limiting riding duration and implementing vibration-reducing technologies in motorcycle design.

Comparison of binocular reading speed in patients with strabismus without amblyopia versus controls

Amblyopia has been shown to slow reading speed. Limited literature exists on reading speed in strabismus without amblyopia. Our study compares binocular reading speed in patients with strabismus without amblyopia versus normal controls. We conducted a prospective study with 48 participants: 12 childhood-onset (onset <8 years of age) strabismus without amblyopia and 36 age- and education level-matched controls. Inclusion criteria were age 14-50 years, education >9 years, primary language English, best-corrected visual acuity >20/30 distance, and >N8 near either eye. Exclusion criteria were presence of other eye pathology or neurologic/cognitive conditions that may affect reading and previous treatment for strabismus/amblyopia. International Reading Speed Texts were used for binocular reading speed assessment. Each participant read 2 passages (passage 1 and 8), following all International Reading Speed Texts instructions. Reading time was measured using a stopwatch. Reading speed was calculated in words per minute (WPM). Mean age for the strabismus group was 28.3 ± 11.1 and for the control group was 28.2 ± 11.0 years (P = 0.96). Mean education level for strabismus group was 14.2 ± 2.4 and control group was 13.8 ± 2.5 years (P = 0.62). Mean binocular reading speed for passage 1 for strabismus group was 192.0 and for control group was 220.0 WPM (P = 0.01). Mean binocular reading speed for passage 8 for strabismus group was 201.3 and for control group was 226.2 WPM (P = 0.04). Patients with strabismus (without amblyopia) had slower binocular reading speed compared with controls. Further studies with eye tracking may provide more information. Strabismus, even without amblyopia, may affect reading performance and consequently vision-related quality of life.

Experimental investigation and parametric optimization of rotary ultrasonic machining of different bio-ceramic materials

Rotary ultrasonic machining (RUM) is a highly promising technique for machining bio-ceramic materials due to its ability to achieve high precision and superior surface quality. This research focuses on an experimental investigation and parametric optimization of RUM for different bio-ceramic materials, intending to optimize multiple machining responses simultaneously. The experimental setup involves utilizing a 3-axis CNC ultrasonic machine to machine three different workpieces with slot cutting. Various machining parameters, such as tool feed rate and tool rotating speed, are studied to determine their impacts. An orthogonal array design based on Taguchi optimization is used to execute the experiments effectively. Material removal rate (MRR) and surface roughness (SR) are monitored and statistically analyzed as a consequence of the responses. ANOVA demonstrates that the tool feed rate has a considerable impact on the output reactions, with material type and tool rotational speed also playing a role. For multiple response optimizations, the Taguchi-Grey method is used to achieve the best trade-off between MRR and Sr The results demonstrate that material type has the most substantial impact on surface roughness, followed by feed rate and spindle speed. In contrast, feed rate has the most significant effect on the material removal rate, followed by the material type and spindle speed. The optimal parameter settings for achieving the desired output parameter are determined. The confirmation experiments validate the effectiveness of the optimized parameters. The feed rate of 5 mm min−1, and spindle speed of 2500 rpm were discovered to be the optimal condition for achieving maximum MRR and minimum Ra. The MRR and surface roughness values were measured as 1.7266 mm3 min−1 and 1.5611 microns respectively.

Extracting typing game keystroke patterns as potential indicators of programming aptitude

This study attempted to determine whether individuals possess programming aptitude solely based on keystroke information from typing games where participants type computer programs. The participants were students enrolled in university programming courses. The results indicated that using typing speed alone as an indicator achieved an accuracy of 0.71, while employing a custom machine learning model achieved an accuracy of 0.83. Additionally, it was found that individuals with programming aptitude tended to type the enter key relatively slower compared to other keys.

Dynamics of high-speed electrical tree growth in electron-irradiated polymethyl methacrylate.

Dielectric materials are foundational to our modern-day communications, defense, and commerce needs. Although dielectric breakdown is a primary cause of failure of these systems, we do not fully understand this process. We analyzed the dielectric breakdown channel propagation dynamics of two distinct types of electrical trees. One type of these electrical trees has not been formally classified. We observed the propagation speed of this electrical tree type to exceed 10 million meters per second. These results identify substantial gaps in the understanding of dielectric breakdown, and filling these gaps is paramount to the design and engineering of dielectric materials that are less susceptible to electrostatic discharge failure.

Investigating the effect of key size, typing angle, and typing technique of virtual keyboard on typing productivity, biomechanics, and usability in a mixed reality environment

This study investigates the effects of key sizes, typing angles, and typing techniques on typing productivity, biomechanics (muscle activity), and subjective experience with a mixed reality keyboard. The findings suggest that using smaller key sizes, such as 16 mm, may not be suitable due to slower typing speed, lower accuracy, lower user experience, higher muscle activity, and higher motion sickness. Typing with both index fingers results in the highest typing speed while using only a single index finger provides higher accuracy. Placing the keyboard at eye height leads to the highest typing speed, as participants can easily view the keys and the virtual environment simultaneously. However, typing accuracy is not affected by typing angle and typing technique. Implementing these findings on the virtual keyboard design could potentially benefit workers’ productivity and decrease errors in the mixed reality environment.

CFD modeling of H2S removal from liquid sulfur in a pilot-scale gas-liquid contactor

Removal of hydrogen sulfide (H2S) from liquid sulfur is essential to product quality and safe operation in sulfur processing recovery. This paper presents computational fluid dynamics (CFD) models of sulfur degassing performance in a pilot-scale gas-liquid contactor. Two mass transfer models with and without considering the decomposition of hydrogen polysulfide (H2Sx) to H2S are established. They are then used to explore the effects of various operating parameters, including residence time, injected liquid sulfur flow rate, impeller type, and agitation speed, on degassing efficiency. Results show that the relative errors between calculation and experimental data are within ±6.2 %. Furthermore, the impeller geometry is optimized, and the efficiencies of three degasser shapes are compared using the verified CFD tool. The optimized impeller structure can increase degassing efficiency by about 9 % compared to the original one. The CFD model can be further improved to guide the design and scale-up of diverse H2S degassers.