Pen Tip Research Articles

Using a Flexible Fountain Pen to Directly Write Organic Semiconductor Patterns with Crystallization Regulated by the Precursor Film.

Organic semiconductor (OSC) films fabricated by meniscus-guided coating (MGC) methods are suitable for cost-effective and flexible electronics. However, achieving crystalline thin films by MGC methods is still challenging because the nucleation and crystal growth processes are influenced by the intertwined interactions among solvent evaporation, stochastic nucleation, and the fluid flow instabilities. Herein, a novel flexible fountain pen with active ink supply is designed and used to print OSCs. This direct-write method allows the flexible pen tip to contact the substrate, maintaining a robust meniscus by eliminating the gap found in conventional MGCs. An in situ optical microscopy observation system shows that the precursor film plays a critical role on the crystallization and the formation of coffee rings and dendrites. The computational fluid dynamics simulations demonstrate that the microstructure of the pen promotes extensional flows, facilitating mass transport and crystal alignment. Highly-aligned ribbon-shaped crystals of a small organic molecule (TIPS-pentacene), as well as a semiconducting polymer (N2200) with highly-ordered orientations, have been successfully printed by the flexible fountain pen. Organic field-effect transistors based on the flexible pen printed OSCs exhibit high performances and strong anisotropic mobility. In addition, the flexible fountain pen is expandable for printing multiple lines or large-area films.

Design and Evaluation of Pen Body Commands

In current pen-based interactive interfaces, the input channels used by the pen are limited, and target selection and command selection are generally separated sequentially. The intermediate time generated by the movement between target selection and command selection operations further increases the overall operation time. When there are many targets or command operations are frequent, the alternating operations between target selection and command selection easily lead to fatigue. In order to reduce fatigue during frequent movements and decrease multitasking time, we propose pen commands, which can improve the current sequential “select-action” interaction. Based on the differences between the movement trajectories of the pen tip and the pen tail when the pen is rotated, we designed three types of pen body commands. Using the continuous interactive tasks of copy and paste as experimental tasks, we investigated the interactive performance of pen body commands in both target-present and target-absent scenarios through quantitative and qualitative analyses. The experimental results indicate that the interaction time for pen body commands is shorter than that for the combination of rubber band selection and menu clicks, with a performance improvement of 70.448%. Additionally, the error rate of pen body commands is also lower. Based on these results, we analyse the effectiveness of pen body commands and provided usage suggestions and application scenarios.

Morphological and Thermal Characterization of Low-Cost Graphene Produced by Electrochemical Exfoliation Method

The low-cost and mass production of graphene has gained importance in recent years. The electrochemical exfoliation method, one of the graphene production methods, is an efficient technique used to obtain low-cost-effective and large quantities of graphene nanosheets. Exfoliation parameters affect the properties of exfoliated graphene nanosheets. In this study, graphene production is fabricated by the method of exfoliation using electrolyte and voltage parameters. For this, a pen tip was used instead of pure platinum, which is very expensive, at the cathode. The structural research was done by X-ray diffraction spectroscopy (XRD), Raman spectroscopy and Fourier Transform Infrared Spectrometer (F-TIR). Morphological analyses were carried out by Scanning Electron Microscopy (SEM). The number of layers and crystallite of graphene layers were estimated. The obtained results were compared with the results of the other similar studies. Analysis results show that low-cost multilayer graphene can be produced by the electrochemical exfoliation method with the electrical parameters.

Influence of Eye Movements on Writing Pressure During Handwriting: A CrossSectional Study

Writing pressure is the pressure applied to the desk when handwriting). Clinical observation of Occupational therapy showed that when many patients with hemiplegia instructed to control writing pressure during writing exercises, they kept their gaze on the pen tip. Based on this phenomenon, we considered that eye movement during writing in patients with hemiplegia might be involved in controlling writing pressure. So, as basic research, we aimed to investigate whether eye movements are involved in the writing pressure during handwriting by healthy participants. The participants were 28 healthy adults (2 men, 26 women, average age 21.8 ± 0.6 years). The task was to draw 10-cm lines from left to right and 20 times from right-to-left. The instruments used were Tracking Glasses (SMI ETG) and an upper limb Coordination Evaluation system Trace coder (SYSNET Co. Ltd.). Based on eye movement data, the participants were classified into “target locking type,” including those who kept looking at the goal from the start, and “close pursuit type,” including those who kept their eyes on the tip of the pen. In the target locking type, fluctuations in the writing pressure per unit of time value increased greatly when the angular velocity of eye movements changed. In the close pursuit type, fluctuations in the writing pressure per unit of time value were seen at the start of drawing but decreased after that. The results showed that the amount of change in the writing pressure per unit of time value fluctuated greatly in the target locking type and was small in the close pursuit type. These findings suggest that eye movements affect writing pressure during line drawing

An Eco-Innovative Green Design Method using the Theory of Inventive Problem Solving and Importance–Performance Analysis Tools—A Case Study of Marker Pen Manufacturing

This study explores innovative designs for the cap of a marker pen, aiming to address the issues of cap loss and ink evaporation during marker pen usage. This study applies intrinsic safety, universal design and TRIZ as research methods. TRIZ has great potential to address most of the Sustainable Development Goals (SDGs) relevant to conflict-oriented problem solving for innovations. The principles of simplification, foolproof design, clarity of states, and tolerance from intrinsic safety were applied to prevent cap loss and minimize the risks associated with ink evaporation. The TRIZ methodology’s contradiction matrix was utilized to identify relevant inventive principles by improving parameters and avoiding worsening parameters, providing a reference basis for product structure design. Lastly, the principles of equitable use, simplicity, intuitiveness, and effortless design from universal design were employed to enhance the marker pen’s usability for the general public. This study creates a SERVQUAL questionnaire to compare the prototype of the designed pen cap with commercially available pen caps. It utilizes the two-dimensional quality model (Kano model) and Importance–Performance Analysis (IPA) for practical design analysis. Finally, the prototype structure is visualized using graphic software. The innovative design features of this study include the following. (1) Concealable pen tip: the sliding seal hides the pen tip inside the pen body when the pen core is slid upwards, preventing cap loss and ink drying. (2) Quick retractable function: using a pressing mechanism, the pen tip can be quickly retracted with a one-handed press and slide motion. (3) Replaceable pen core: the pen core can be replaced by disassembling the pen body, removing the old pen core, and inserting a new one, thereby extending the pen’s lifespan. (4) Satisfaction evaluation of the innovative pen cap design: through questionnaire surveys and cross-analysis using the IPA and the Kano model, this study assesses the product’s manufacturing and mass production value to reduce actual product development costs and time.

Optimization of bubble sheet shading using an infrared technology based pen

Almost everyone feels nervous or at least experiences some levels of anxiety in exams or quizzes. Nowadays people find all exams turns to multiple choice questions as it is more useful to ensure students’ understanding. Shading the bubble sheet is a big problem for most students because it takes long time, accordingly this will affect the anxiety's level of students. In addition, Optical Mark Recognition (OMR) systems appear to make exams’ marking faster and easier, leading to save the professors effort. This paper discusses a solution for the problem of feeling anxious and the wasted time in answering and marking exams by designing a unique pen. Additionally, it regards the need of making use of exam time by changing the used pen tip diameter. This gives the ability of shading in one pen press. Also, an alarm electronic circuit is added to avoid any mistakes in shading. Besides, an erasing mechanism is performed to make it easier if the student decides to change his answer. Consequently, bubble sheet exams will be easy for both students and professors. As a result, the proposed pen is time efficient as it gives approximately 70 % efficiency over the ordinary pen.

Offline Handwritten Chinese Character Using Convolutional Neural Network: State-of-the-Art Methods

Given the presence of handwritten documents in human transactions, including email sorting, bank checks, and automating procedures, handwritten characters recognition (HCR) of documents has been invaluable to society. Handwritten Chinese characters (HCC) can be divided into offline and online categories. Online HCC recognition (HCCR) involves the trajectory movement of the pen tip for expressing linguistic content. In contrast, offline HCCR involves analyzing and categorizing the sample binary or grayscale images of characters. As recognition technology develops, academics’ interest in Chinese character recognition has continuously increased, as it significantly affects social and economic development. Recent development in this area is promising. However, the recognition accuracy of offline HCCR is still a sophisticated challenge owing to their complexity and variety of writing styles. With the advancement of deep learning, convolutional neural network (CNN)-based algorithms have demonstrated distinct benefits in offline HCCR and have achieved outstanding results. In this review, we aim to show the different HCCR methods for tackling the complexity and variability of offline HCC writing styles. This paper also reviews different activation functions used in offline HCCR and provides valuable assistance to new researchers in offline Chinese handwriting recognition by providing a succinct study of various methods for recognizing offline HCC.

Implementation of a Fusion Classification Model for Efficient Pen-Holding Posture Detection

Pen-holding postures (PHPs) can significantly affect the speed and quality of writing, and incorrect postures can lead to health problems. This paper presents and experimentally implements a methodology for quickly recognizing and correcting poor writing postures using a digital dot matrix pen. The method first extracts basic handwriting information, including page number, handwriting coordinates, movement trajectory, pen tip pressure, stroke sequence, and pen handling time. This information is then used to generate writing features that are fed into our proposed fusion classification model, which combines a simple parameter-free attention module for convolutional neural networks (CNNs) called NetworkSimAM, CNNs, and an extension of the well-known long short-term memory (LTSM) called Mogrifier LSTM or MLSTM. Finally, the method ends with a classification step (Softmax) to recognize the type of PHP. The implemented method achieves significant results through receiver operating characteristic (ROC) curves and loss functions, including a recognition accuracy of 72%, which is, for example, higher than that of the single-stroke model (i.e., TabNet incorporating SimAM). The obtained results show that a promising solution is provided for accurate and efficient PHP recognition and has the potential to improve writing speed and quality while reducing health problems induced by incorrect postures.

Automatic diagnosis of multi-task in essential tremor: Dynamic handwriting analysis using multi-modal fusion neural network

Essential tremor (ET) is one of the most common movement disorders, and patients with ET have more than a fourfold increased risk of developing Parkinson’s disease (PD). Currently, the handwriting assessment remains the gold standard for ET diagnosis and quantification of tremor severity. However, the traditional evaluation of tremors is subjective and partial, primarily limited by the experience of the neurologist and the progression of the disease course. With advanced sensing and computer technology development, digital pad-based electronic handwriting analysis can provide clinical information on pen tip kinematics. This study proposes a novel spatial–temporal–spectral fusion neural network (STSNet) for multi-task fine-grained assessment of tremor severity. The model can efficiently fuse complementary information from static handwriting images and dynamic multi-sensory fusion signals. Specifically, we design a static spatial branch for learning the global spatial features of the electronic handwriting image and a dynamic temporal branch to learn the spectrogram features in the time–frequency domain. The spectrograms are obtained by the transformation algorithm of the kinematic signals of the nib sensors to represent the spectral energy associated with tremor. In addition, we also validate the utility of the attention mechanism, transfer learning strategy, and the introduction of demographic features-based prior knowledge by ablation studies. STSNet obtains an average accuracy of 97.33–97.39%​ (five categories) on our collected database containing 147 ET patients. In addition, we test the robustness and effectiveness of the proposed method in three publicly available databases of PD diagnostics. These results show that STSNet outperforms other advanced works, which can automatically provide objective and accurate scores for ET symptom assessment or PD diagnosing.

Extremely long nanojet formation from a ballpoint photonic pen

Certain microelements can facilitate light manipulation in the form of an intense electromagnetic beam known as a “photonic nanojet” (PNJ), which is an emerging candidate in the field of spectroscopy, nanolithography, and bio/chemical sensing. However, inherent limitations of the PNJs such as short jet length, focal point, and working length minimize their application areas. Herein, by considering readily available materials and technologies, we report a simple and physically realizable “photonic pen” (PP)-like microstructure to yield extremely long PNJs under plane-wave illumination. Essentially, by semi-immersing a sphere of certain diameter (acting as pen tip) in a barrel material with the width equal to and height 5 times the sphere diameter, a “ballpoint pen”-like microstructure is formed where illuminated light acts as the ink. Finite-difference time-domain analysis shows the use of low refractive index (RI) spherical tips ( n = 1.48 ) with 10 µm diameter, and a high RI SU-8 barrel ( n = 1.62 ) creating a net index difference of Δ n = 0.14 to effectively form PNJs with extremely long jet length, working distance, and full width at half-maximum of over 330 λ (121.6 µm), 319.45 λ (116.6 µm), and 4.22 λ (1.54 µm) respectively, and a figure of merit of ∼ 155 in water environment. S i O 2 / SU- 8 PPs show over ∼ 3 times longer jet length than previous studies. We show that such SU- 8 / SiO 2 PPs with extremely long PNJs can act as epidermal photonic imagers to scan biological tissues such as trilayer human skin to detect melanoma (skin cancer), both in contact and in noncontact mode with efficiency enhancement reaching ∼ 45 % compared to plain microspheres without barrels.

Application of Absorption Spectra to Study Order of Sequence in Intersecting Printed and Pen Strokes

This work is performed to establish chronological order in crossing strokes between printed stroke and pen strokes. Nine different types of pens including cello maxriter pen (black and blue), pilot pen (red and black), cello pointec pen (black and blue) and cello techno tip pen (red, black and blue) are used to produce pen strokes and for printed stroke Canon LBP 3300 printer is used. In the case of printed stroke, only black color stroke is applied. As a result, samples of both homogeneous and heterogeneous intersecting strokes are prepared. This work is based on the assumption that nature and peak characteristics of absorption spectra from crossing stroke should be similar to that of second stroke. Here, absorption spectra is generated by Video Spectral Comparator-6000 by using light of wavelength ranging from 400 nm to 1000 nm. From this experiment, it is found to be possible to find chronological order for heterogeneous crossing strokes (crossing stroke of different colors) only if printed stroke is over pen stroke. It means, only if print is done over writing strokes from red and blue pen, then order of sequence of writing can be determined whereas in other cases it is not possible.

Acoustic Sensing Based on Online Handwritten Signature Verification

Handwritten signatures are widely used for identity authorization. However, verifying handwritten signatures is cumbersome in practice due to the dependency on extra drawing tools such as a digitizer, and because the false acceptance of a forged signature can cause damage to property. Therefore, exploring a way to balance the security and user experiment of handwritten signatures is critical. In this paper, we propose a handheld signature verification scheme called SilentSign, which leverages acoustic sensors (i.e., microphone and speaker) in mobile devices. Compared to the previous online signature verification system, it provides handy and safe paper-based signature verification services. The prime notion is to utilize the acoustic signals that are bounced back via a pen tip to depict a user's signing pattern. We designed the signal modulation stratagem carefully to guarantee high performance, developed a distance measurement algorithm based on phase shift, and trained a verification model. In comparison with the traditional signature verification scheme, SilentSign allows users to sign more conveniently as well as invisibly. To evaluate SilentSign in various settings, we conducted comprehensive experiments with 35 participants. Our results reveal that SilentSign can attain 98.2% AUC and 1.25% EER. We note that a shorter conference version of this paper was presented in Percom (2019). Our initial conference paper did not finish the complete experiment. This manuscript has been revised and provided additional experiments to the conference proceedings; for example, by including System Robustness, Computational Overhead, etc.

Participatory design and needs assessment for a pressure-sensitive pen and mobile application (SensoGrip) for children with handwriting problems

Purpose Problems with handwriting are a common referral to occupational therapy in children and are often associated with inadequate pen grip and tip pressure. Technologies providing immediate feedback on applied forces are currently not available. Therefore, the aim was to identify user’s perspectives on the optimal functionality of a pressure-sensitive pen with an integrated feedback system. Methods To ensure that the product meets the requirements of the users, user needs of paediatric occupational therapists, elementary or special education teachers and children were collected in two focus groups and a children’s workshops before starting the technical development process. Focus group transcripts were analyzed and rephrased as user stories to identify user-centred requirements. In a second step, user stories were merged and ranked regarding importance and feasibility. Results 120 user story requirements were generated from the focus groups and children’s workshops, indicating requirements regarding design and functionality for the pen and mobile application. Visual feedback, appropriate size and weight, customizability, ease of settings and usability of the pen were pivotal. Conclusions This study comprehensively researched the requirements for a device that may facilitate children in adjusting their handwriting pressure and can guide further research and evaluation.

Ultra-fast-responsivity with sharp contrast integrated flexible piezo electrochromic based tactile sensing display

Flexible pressure sensitive electronic skins have attracted great attention for motion detection and medical health in recent years. Conventional display systems require complicated design, complex procedure, and advanced equipment, which limit their use and lower the cost. Herein, we present an integrated piezo electrochromic based tactile sensing display (PETSD) with polyvinylidene fluoride (PVDF) matrix as pressure sensor and polyaniline electrochromic array as display modulus. The display clearly and reliably demonstrates the movement track of finger or a pen tip in real time, record, and recovery spanning from transparent to dark blue under various pressing force with the record and recovery responsive speed of as low as 1.4 s and a color contrast of 62.2% due to the excellent memory effect of polyaniline. PETSD exhibits an extremely durable property and cycle stability maintaining 94.9% of its color contrast after 1600 s continuous cycle. The innovative PETSD provides a low power consumption based on organic electrochromic device (OECD) which may find prospective applications in various field of flexible optoelectronic devices, interactive wearable systems and intelligent robots.

Surface-Free Multi-Stroke Trajectory Reconstruction and Word Recognition Using an IMU-Enhanced Digital Pen.

Efficient handwriting trajectory reconstruction (TR) requires specific writing surfaces for detecting movements of digital pens. Although several motion-based solutions have been developed to remove the necessity of writing surfaces, most of them are based on classical sensor fusion methods limited, by sensor error accumulation over time, to tracing only single strokes. In this work, we present an approach to map the movements of an IMU-enhanced digital pen to relative displacement data. Training data is collected by means of a tablet. We propose several pre-processing and data-preparation methods to synchronize data between the pen and the tablet, which are of different sampling rates, and train a convolutional neural network (CNN) to reconstruct multiple strokes without the need of writing segmentation or post-processing correction of the predicted trajectory. The proposed system learns the relative displacement of the pen tip over time from the recorded raw sensor data, achieving a normalized error rate of 0.176 relative to unit-scaled tablet ground truth (GT) trajectory. To test the effectiveness of the approach, we train a neural network for character recognition from the reconstructed trajectories, which achieved a character error rate of 19.51%. Finally, a joint model is implemented that makes use of both the IMU data and the generated trajectories, which outperforms the sensor-only-based recognition approach by 0.75%.

Bigger Is Not Always Better: Effects of Electrocautery Setting on Tissue Injury in a Porcine Model.

IntroductionElectrosurgery for dissection and hemostasis remains one of the foundational tools for the field of surgery as a whole. Monopolar cautery remains the most utilized modality for achieving the aforementioned goals. Given the prolonged history and pre-modern development of "Bovie" cautery, there remains a paucity of data regarding appropriate settings and intensity for various tissue types, procedures, or locales. As a result, utilized settings depend on precedent and personal preference. We aimed to determine the amount of secondary soft tissue injury by volume and depth beyond the electrocautery pen tip in the skin and subcutaneous tissue as well as skeletal muscle. MethodsPorcine samples were used for experimental testing using two testing types: 1) skin and subcutaneous tissue and 2) Skeletal muscle. Sample sizes were standardized at 1 cm3 cubes. For skin samples, tissue injury was created with either a scalpel or electrocautery pen on cut setting, and tested at intensities from 10 to 150 in increments of 10. Skeletal muscle samples were similarly tested using the electrocautery pen only in either a cut or coagulation setting. Samples were tested at incremental intensities from 10 to 120 for both settings. Electrocautery was tested for a period of five seconds with a continuous current. All samples were placed in formalin and underwent histologic staining with hematoxylin and eosin staining to be assessed for the extent of tissue injury in terms of depth, radius, and volume. The measurements were recorded in millimeters.ResultsFor skin incision, there was a positive and significant correlation with respect to the radius (R=.73, p=0.006). When considering intensity with an interval of 10-70 there was a positive and significant correlation with respect to the radius, depth, and volume. The cold knife incision had no notable soft tissue injury beyond the depth of the incision. Regarding skeletal muscle, again, a significant and positive correlation between increasing monopolar settings was noted for both the coagulation and cut functions (R=.84, p=.0005; R=0.84, p=0.0006). A positive correlation was found between increasing cut intensity and volume of soft tissue injury (R=0.73, p=.008); this was not reflected in the coagulation setting. When limited to an intensity range of 10-60, a significant relationship was noted for depth, radius and volume (R=.95, p= <0.001; R=0.98, p= <.001; R=.92, p=.001).ConclusionIn all samples, apart from the cold knife skin incision, additional soft tissue injury beyond the tip of the electrocautery pen was noted. Given our findings, recommendations include using the lowest setting required for the purposes of the given surgical case as well as minimizing electrocautery use for skin incisions given its association with a larger volume of tissue injury in comparison with a scalpel. Additionally, electrocautery should be used with care in, and around neurovascular structures as soft tissue injury did occur several millimeters beyond the tip of the electrocautery pen. Further study is needed to see if these patterns are similar in living animals as well as human tissue and whether they bear any clinical impact on surgical wound healing or other surgical complications.

Pen-grip kinetics in children with and without handwriting difficulties.

Handwriting difficulty (HD) is a widely discussed issue. Previous researchers have revealed many valuable kinematics related to the handwriting performance. However, a clear understanding of the kinetics of handwriting performance in children with HD is still lacking. Therefore, this study investigated the writing performance of children with HD via a force acquisition pen (FAP), which detects the force applied from the digits and pen tip. Data from 64 school-age children were divided into control (36 children without HD; mean age: 7.97 years) and HD (28 children with HD; mean age: 8.67 years) groups. The participants were asked to perform a tracing task using the FAP at their usual writing pace. Compared with the control group, the HD group had significantly less pen-tip force, an average amount of force (in-air) from all three digits, higher force variations (whole task) in the index finger, less force fluctuations with the index and middle fingers and a smaller force ratio. The findings of this study suggest that an understanding of the handwriting kinetics and the role of digits in handwriting may be crucial for further planning strategies for handwriting training for children with HD.

Exam Marks Summation App Using Tesseract OCR in Python

There are no tools to auto grade subjective questions and no auto summations app to date. As a result, examiners need to mark subjective answer scripts manually and they might overlook some marks while summing up subjective answer scripts scores obtained by students. Therefore, this study aims to develop an exam mark summation app to ease miscalculation problems. Tesseract OCR was implemented in this Marks Summation App as a platform to scan the multi-page handwritten marks using pen tip above a 0.5mm size in red, blue, and black to recognise the marks wrote by the examiners. The captured marks images will be uploaded to server for image processing by promptly executing the python script in the server. The extraction of numbers from the processed image will sum up the scores to determine each candidate's final score. It is recommendable to scan the original materials to produce more accurate accuracy. Out of 118 numbers from 21 testing samples, 88 numbers are correctly recognised, whereas 30 are not recognised correctly. Thus, the accuracy of the developed exam mark summation app is 74.58%. The app's performance is more superior than car plate recognition result in the field. In the future, we hope to increase the app’s recognition accuracy by exploring deep learning in recognizing handwritten numbers.

Robust Robotic 3-D Drawing Using Closed-Loop Planning and Online Picked Pens

This article develops a flexible and robust robotic system for autonomously drawing on 3-D surfaces. The system takes 2-D drawing strokes and a 3-D target surface (mesh or point clouds) as input. It maps the 2-D strokes onto the 3-D surface and generates a robot motion to draw the mapped strokes using visual recognition, grasp pose reasoning, and motion planning. The system is flexible compared to conventional robotic drawing systems as we do not fix drawing tools to the end of a robot arm. Instead, a robot recognizes and picks up pens online and holds the pens to draw 3-D strokes. Meanwhile, the system has high robustness thanks to the following crafts: First, a high-quality mapping method is developed to minimize deformation in the strokes. Second, visual detection is used to reestimate the drawing tool&#x2019;s pose before executing each drawing motion. Third, force control is employed to compensate for noisy visual detection and calibration and ensure a firm touch between the pen tip and the surface. Fourth, error detection and recovery are implemented to deal with slippage and other anomalies. The planning and executions are performed in a closed-loop manner until the strokes are successfully drawn. We evaluate the system and analyze the necessity of the various crafts using different real-world tasks. The results show that the proposed system is flexible and robust to generate robotic motion that picks up the pens and successfully draws 3-D strokes on given surfaces.

Validation of dementia diagnostics toolbox using interactive iPad technology

AbstractBackgroundConventional means for dementia diagnosis rely on qualitative tests usually administered after significant pathogenesis. Past studies suggest the utility of more quantitative analytical approaches such as handwriting/drawing tasks (Impedevo et al., 2018). Such tools would provide low‐cost, portable, and instantaneous quantitative diagnostics for more efficient patient screening. However, efforts to realize these methods have faced challenges such as low sample size, incomplete feature extraction, and lack of task diversity. We attempted to create a tablet application that uses pen‐tracking technology to surmount these challenges.MethodAs fine motor control provides fundamental markers of neurological health (Bisio et al., 2017; Thomas et al., 2017), rigorous statistical analysis of simple drawing tasks on a tablet permitted differentiation between neuronormative patients and dementia patients with high fidelity. We have started testing our data analysis pipeline with open access datasets: PaHaW (Drotár et al., 2016), Isuniba (Impedovo et al, 2013), ParkinsonHW (Isenkul et al., 2014). These datasets contain drawing data for healthy individuals and those with both dementia and other neurodegenerative diseases. They contain similar raw data that the in‐house iPad app collects. From that raw data, we extracted predictive features, including velocity, acceleration, jerk, curvature, and measures of variation.ResultWe have successfully created an iPad app that is able to record the dynamic handwriting process with an Apple Pencil. Our platform has the potential to generate more standardized datasets with improved documentation compared to existing archives. Patients trace complex figures such as spirals and infinity symbols at varying speeds over multiple trials. Additionally, the subjects are asked to remember and draw a shape that was presented to them at the beginning of the test. The app collects key data such as the position of the pen tip, velocity of pen movement, pen angle relative to the surface, and pressure exerted on the surface.ConclusionWe plan to deploy our in‐house iPad app in clinical trials to collect pen‐tracking data with which to facilitate differential diagnoses for neurodegenerative diseases afflicting Alzheimer’s and Parkinson’s patients. The validation of such a platform would improve upon existing diagnostic datasets and lower major barriers to dementia screening.