Smartphone Touchscreen Research Articles

Giving a face to remote management - the digital future of physiotherapy

Purpose: The Five Year Forward View report highlighted the need to take advantage of opportunities technology offers patients. 81% of UK Adults (91% 18-44) have touch screen smart phones with the majority (89%) 4G enabled.

Interaction with touchscreen smartphones in patients with essential tremor and healthy individuals

IntroductionSmartphone use in biomedical research is becoming more prevalent in different clinical settings. We performed a pilot study to obtain information on smartphone use by patients with essential tremor (ET) and healthy controls, with a view to determining whether performance of touchscreen tasks is different between these groups and describing touchscreen interaction factors. MethodA total of 31 patients with ET and 40 sex- and age-matched healthy controls completed a descriptive questionnaire about the use of smartphones. Participants subsequently interacted with an under-development Android application, and performed 4 tests evaluating typical touchscreen interaction gestures; each test was performed 5 times. ResultThe type of smartphone use and touchscreen interaction were not significantly different between patients and controls. Age and frequency of smartphone use are key factors in touchscreen interaction. ConclusionOur results support the use of smartphone touchscreens for research into ET, although further studies are required.

Microbiological contamination in Smartphones

Smartphones tornaram-se um dos dispositivos essenciais mais utilizados para a comunicação diária. Raramente esses dispositivos são desinfetados, podendo ocorrer contaminação com vários agentes microbianos. Amostras coletadas nas telas touch screen de smartphones foram analisadas para determinar a contagem de bactérias aeróbias mesofílicas, enterobactérias, bolores e leveduras, bactérias coliformes totais e bactérias coliformes a 45 °C. Mais de 70% dos aparelhos analisados apresentaram contaminação elevada por bactérias mesófilas aerofílicas e bolores e leveduras, além de 25% por enterobactérias, sendo observada a presença de coliformes a 45 °C em 25% dos aparelhos avaliados. A elevada contaminação por mesófilos aeróbios e bolores e leveduras e a presença de enterobactérias e bactérias coliformes a 45 °C sugerem um risco à saúde dos usuários devido à possível presença de organismos patogênicos.

Interacción con pantalla táctil de smartphone en pacientes con temblor esencial y sujetos sanos

IntroductionSmartphones use in biomedical research is becoming more prevalent in different clinical settings. We performed a pilot study to obtain information on smartphone use by patients with essential tremor (ET) and healthy controls, with a view to determining whether performance of touchscreen tasks is different between these groups and describing touchscreen interaction factors. MethodA total of 31 patients with ET and 40 sex- and age-matched healthy controls completed a descriptive questionnaire about the use of smartphones. Participants subsequently interacted with an under-development Android application, and performed 4 tests evaluating typical touchscreen interaction gestures; each test was performed 5 times. ResultThe type of smartphone use and touchscreen interaction were not significantly different between patients and controls. Age and frequency of smartphone use are key factors in touchscreen interaction. ConclusionOur results support the use of smartphone touchscreens for research into ET, although further studies are required.

Touchscreen typing-pattern analysis for detecting fine motor skills decline in early-stage Parkinson\u2019s disease

Parkinson’s disease (PD) is a degenerative movement disorder causing progressive disability that severely affects patients’ quality of life. While early treatment can produce significant benefits for patients, the mildness of many early signs combined with the lack of accessible high-frequency monitoring tools may delay clinical diagnosis. To meet this need, user interaction data from consumer technologies have recently been exploited towards unsupervised screening for PD symptoms in daily life. Similarly, this work proposes a method for detecting fine motor skills decline in early PD patients via analysis of patterns emerging from finger interaction with touchscreen smartphones during natural typing. Our approach relies on low-/higher-order statistical features of keystrokes timing and pressure variables, computed from short typing sessions. Features are fed into a two-stage multi-model classification pipeline that reaches a decision on the subject’s status (PD patient/control) by gradually fusing prediction probabilities obtained for individual typing sessions and keystroke variables. This method achieved an AUC = 0.92 and 0.82/0.81 sensitivity/specificity (matched groups of 18 early PD patients/15 controls) with discriminant features plausibly correlating with clinical scores of relevant PD motor symptoms. These findings suggest an improvement over similar approaches, thereby constituting a further step towards unobtrusive early PD detection from routine activities.

Intelligent Touchscreen Joystick for Controlling Electric Wheelchair

BackgroundThe objective of this research was to design, implement, use and evaluate a human-machine touch interface for driving an electric wheelchair. This new interface allows control of the electric wheelchair with touch screen smartphone technologies (android, IOS or Windows phone). In addition, an intelligent calibration algorithm, based on the neural network (NN), is implemented in this interface to overcome manoeuvring problems, namely the inability to move correctly in one or more directions. MethodsOur work offers a touch screen human-machine interface for controlling the electric wheelchair. Three patients aged 15 to 66 years participated in our experiment. They were asked to control the electric wheelchair using two types of interface (the standard mechanical joystick and the intelligent touch screen joystick we offer) according to the established protocol. This allowed us to extract the benefits of using the calibrated touch interface to move the wheelchair. The advantage of this control is that it allows the patient to drive the wheelchair with a precise variable speed like a traditional motorized joystick with less effort.We have set up a two-way communication between the tablet and the control system. This allows us not only to control the wheelchair, but also to detect and treat communication errors as a sudden disconnection. In this case, the wheelchair stops and waits for the user to take further action. The use of Wi-Fi has many advantages since it is a lighting solution and the user can even park the wheelchair in his room when he is lying in bed. ResultsWe can notice that users are faster with the intelligent touch joystick than with the mechanical joystick. This is because less muscular effort is required on the first than on a mechanical joystick, the user only uses his finger to move the chair. Moreover, the advantage of using the neural network ensures increased speed and stability of movement even if the user has the impression that his finger is in the wrong direction on the interface and that his speed is reduced because of his pathology. In fact, one of the expected results was that the tablet maintained constant speed longer than the standard mechanical joystick. This can be explained by the fact that it is easier with the tablet to maintain a maximum speed while correcting the trajectory deviation with a minimum effort. ConclusionIn this article, we explored an intelligent touchscreen solution that will address the problems faced by our target users. We conducted a thorough research on the types of existing control interfaces. We found that most of these interfaces use a discrete control of speed and direction. After testing it with a group of disabled users, we noticed the importance of analogic control. As part of our iterative design approach, we designed a prototype that provides this analogic control and in which we have implemented a calibration algorithm based on the neural networks algorithm.

Texting with touchscreen and keypad phones - A comparison of thumb kinematics, upper limb muscle activity, exertion, discomfort, and performance

This study aimed to compare thumb kinematics and upper limb muscle activity, and the influence of hand size, when texting on a keypad smartphone and a touchscreen smartphone. Furthermore, the study compared exertion, discomfort, and performance when texting on the two phones. The thumb kinematics were tracked using a 3D motion analysis system and muscle activity was registered in six upper limb muscles using surface electromyography in 19 participants. When texting on the touchscreen phone compared to the keypad phone thumb flexion (p = 0.008) and flexion/extension range of motion were smaller (p = 0.02), the thumb was on average less internally rotated (p = 0.02), and activity (50th and 90th percentile) of the thumb and forearm muscles was lower (p ≤ 0.05). The differences in thumb flexion were found only in the group with shorter hands and the differences in muscle activity was found only in the group with longer hands. These findings suggest there are differences in risks for developing musculoskeletal disorders during smartphone use with different key activation mechanisms and different hand sizes.

The details of past actions on a smartphone touchscreen are reflected by intrinsic sensorimotor dynamics

Unconstrained day-to-day activities are difficult to quantify and how the corresponding movements shape the brain remain unclear. Here, we recorded all touchscreen smartphone interactions at a sub-second precision and show that the unconstrained day-to-day behavior captured on the phone reflects in the simple sensorimotor computations measured in the laboratory. The behavioral diversity on the phone, the speed of interactions, the amount of social & non-social interactions, all uniquely influenced the trial-to-trial motor variability used to measure the amount of intrinsic neuronal noise. Surprisingly, both the motor performance and the early somatosensory cortical signals (assessed using EEG in passive conditions) became noisier with increased social interactions. Inter-individual differences in how people use the smartphone can help thus decompose the structure of low-level sensorimotor computations.

Microbial Contamination of Smartphone Touchscreens of Italian University Students.

In this study, the microbial contamination of smartphones from Italian University students was analyzed. A total of 100 smartphones classified as low, medium, and high emission were examined. Bacteria were isolated on elective and selective media and identified by biochemical tests. The mean values of cfu/cm2 were 0.79 ± 0.01; in particular, a mean of 1.21 ± 0.12, 0.77 ± 0.1 and 0.40 ± 0.10cfu/cm2 was present on smartphones at low, medium, and high emission, respectively. The vast majority of identified microorganisms came from human skin, mainly Staphylococci, together with Gram-negative and positive bacilli and yeasts. Moreover, the main isolated species and their mixture were exposed for 3h to turned on and off smartphones to evaluate the effect of the electromagnetic wave emission on the bacterial cultivability, viability, morphology, and genotypic profile in respect to the unexposed broth cultures. A reduction rate of bacterial growth of 79 and 46% was observed in Staphylococcus aureus and Staphylococcus epidermidis broth cultures, respectively, in the presence of turned on smartphone. No differences in viability were observed in all detected conditions. Small colony variants and some differences in DNA fingerprinting were detected on bacteria when the smartphones were turned on in respect to the other conditions. The colonization of smartphones was limited to human skin microorganisms that can acquire phenotype and genotypic modifications when exposed to microwave emissions.

Effects of Shoulder Taping on Discomfort and Electromyographic Responses of the Neck While Texting on a Touchscreen Smartphone.

BackgroundProlonged neck flexion during smartphone use is known as a factor of neck pain and alteration of neck muscle activity. Studies on the effects of shoulder taping on neck discomfort and neck muscle responses while texting on a smartphone are still lacking. The aim of this study was to examine the effects of shoulder taping on neck discomfort using a numerical rating scale, and neck muscle activity and fatigue using a surface electromyography during a texting task on a touchscreen smartphone.MethodsTwenty-five healthy adolescents used the dominant hand to perform a 30-minute texting task using a touchscreen smartphone at two separate times under one of the following two conditions: taping across the upper trapezius muscle and no taping. Neck discomfort, normalized root mean square, and normalized median frequency slopes for upper trapezius, cervical erector spinae, and sternocleidomastoid muscles were recorded.ResultsThe results revealed that shoulder taping provided significantly lower neck discomfort than no taping (p < 0.001). However, shoulder taping did not significantly alter normalized root mean square and normalized median frequency slope values of all muscles when compared with no taping controls.ConclusionShoulder taping reduces neck discomfort but does not affect neck muscle activity and fatigue while texting on a touchscreen smartphone.

Blind users’ expectations of touch interfaces: factors affecting interface accessibility of touchscreen-based smartphones for people with moderate visual impairment

Although current touchscreen-based smartphones are equipped with some accessibility functions for visually impaired people, these users still face substantial challenges, particularly when using smooth touchscreens. In this study, the accessibility factors of touchscreen interfaces for people with visual impairment were explored through principal components analysis. A total of 32 persons with moderate visual impairment and an average age of 35.6 years (SD = 1.62) participated. The accessibility requirements and user experiences of smartphone touchscreen interfaces were collected. The results indicate that touchscreen interfaces have six major accessibility factors. In addition, the operational style of touchscreen interfaces should be redesigned according to a two-stage process. Furthermore, the design guidelines for accessible touchscreen interfaces that meet the requirements of people with visual impairments are summarised. The findings provide an essential reference for product designers constructing accessible touchscreen interfaces, and reinforce the concept of equality in product use.

Exercise training and postural correction improve upper extremity symptoms among touchscreen smartphone users.

Background:Repetitive movements and poor posture are associated with over-use of smartphones when texting or playing games and significantly contribute to the symptoms of pain and discomfort in the upper extremities.Objective:This study investigated the effect of exercise training and postural correction on disabilities of the arm, shoulder, and hand (DASH), hand grip and key pinch strength among smartphone users.Methods:One hundred university students were randomly divided into two groups; the experimental group participated in a 12-week programme of exercise training and postural corrections. The control group were instructed to follow their usual routine for smartphone utilization. Measurements of DASH scores, hand grip strength, and key pinch grip strength were conducted before and after 12 weeks for both groups.Results:There were no significant differences between the start values of both groups for DASH scores, hand grip strength, and key pinch strength (p > 0.05). However, there was a significant improvement in all outcomes measured in the experimental group (p < 0.05), with significant changes in the outcomes of the control group.Conclusion:Postural correction combined with a selected exercise training programme improved the hand grip, key pinch grip strength, and upper extremity disability and symptoms associated with smartphone use among university students.

Recognizing the Operating Hand and the Hand-Changing Process for User Interface Adjustment on Smartphones.

As the size of smartphone touchscreens has become larger and larger in recent years, operability with a single hand is getting worse, especially for female users. We envision that user experience can be significantly improved if smartphones are able to recognize the current operating hand, detect the hand-changing process and then adjust the user interfaces subsequently. In this paper, we proposed, implemented and evaluated two novel systems. The first one leverages the user-generated touchscreen traces to recognize the current operating hand, and the second one utilizes the accelerometer and gyroscope data of all kinds of activities in the user’s daily life to detect the hand-changing process. These two systems are based on two supervised classifiers constructed from a series of refined touchscreen trace, accelerometer and gyroscope features. As opposed to existing solutions that all require users to select the current operating hand or confirm the hand-changing process manually, our systems follow much more convenient and practical methods and allow users to change the operating hand frequently without any harm to the user experience. We conduct extensive experiments on Samsung Galaxy S4 smartphones, and the evaluation results demonstrate that our proposed systems can recognize the current operating hand and detect the hand-changing process with 94.1% and 93.9% precision and 94.1% and 93.7% True Positive Rates (TPR) respectively, when deciding with a single touchscreen trace or accelerometer-gyroscope data segment, and the False Positive Rates (FPR) are as low as 2.6% and 0.7% accordingly. These two systems can either work completely independently and achieve pretty high accuracies or work jointly to further improve the recognition accuracy.

Graphical Password-Based User Authentication With Free-Form Doodles

User authentication using simple gestures is now common in portable devices. In this work, authentication with free-form sketches is studied. Verification systems using dynamic time warping and Gaussian mixture models are proposed, based on dynamic signature verification approaches. The most discriminant features are studied using the sequential forward floating selection algorithm. The effects of the time lapse between capture sessions and the impact of the training set size are also studied. Development and validation experiments are performed using the DooDB database, which contains passwords from 100 users captured on a smartphone touchscreen. Equal error rates between 3% and 8% are obtained against random forgeries and between 21% and 22% against skilled forgeries. High variability between capture sessions increases the error rates.

Thumb performance of elderly users on smartphone touchscreen.

This study investigated the relationship between thumb muscle activity and thumb operating tasks on a smartphone touchscreen in elderly users (right hand posture). Three thumb muscles were targeted in the experiment, namely, abductor pollicis brevis, abductor pollicis longus (APL) and first dorsal interosseous (FDI). The results showed that the elderly participants developed fatigue rapidly and tapped more slowly when operating on smaller buttons (diameter 3.0 mm compared with 9.0 mm) and moving in the flexion–extension (compared with adduction–abduction) orientation. Meanwhile, electromyography and perceived exertion evaluation revealed significant increases in FDI in the small button task, and results for APL were significantly greater in the flexion–extension task. This study suggests that the use of small touch-buttons and flexion–extension movement should be minimised in the handheld touchscreen interface design for elderly users.

Analyzing visually impaired people’s touch gestures on smartphones

We present an analysis of how visually impaired people perform gestures on touch-screen smartphones and report their preferences, explaining the procedure and technical implementation that we follo...

A Participatory Design and Formal Study Investigation into Mobile Text Entry for Older Adults

Text entry remains key to many tasks on touchscreen smartphones and is an important factor in the usability of such devices. The known problems of text entry can be particularly acute for older adults due to physical and cognitive issues associated with ageing. In a study of mobile text entry the authors employed a variety of participatory design and formal comparative study techniques in order to explore the requirements of this group of users and to discover the key differences in texting activity between them and younger users of mobile devices. They report on the findings of a lab study of texting behaviour of older adults. The authors' findings indicate differences in attitudes to texting styles and tasks between older and younger adults. They also identify some differences in typing behaviour and reflect on methods.

Performance Analysis of Touch-Interaction Behavior for Active Smartphone Authentication

The increasing use of touchscreen smartphones to access sensitive and privacy data has given rise to the need of secure and usable authentication technique. Smartphone users have their own unique behavioral characteristics when performing touch operations. These personal characteristics are reflected on different rhythm, strength, and angle preferences of touch-interaction behavior. This paper investigates the reliability and applicability on the usage of users’ touch-interaction behavior for active authentication on smartphones. For each common type of touch operations, both static and dynamic features are extracted and analyzed for fine-grained characterization of users’ touch behavior. Classification techniques (nearest neighbor, neural network, support vector machine, and random forest) are applied to the feature space for performing the task of active authentication. Analyses are conducted using data from around 134 900 touch operations of 71 participants in real-world scenarios, and the authentication performance is evaluated across various types of touch operations, varying operation lengths, different application tasks, and different application scenarios. The extensive experimental results are included to show that touch-interaction behavior exhibits sufficient discriminability and stability among smartphone users for active authentication, and achieves equal-error rates between 1.72% and 9.01% for different types of touch operations with the operation length of 11; the authentication accuracies improve when having long observation or small timespan between the training and testing phases, and express more reliably and stably in a specific task than in the free task. We also discuss a number of avenues for additional research that we believe are necessary to advance the state-of-the-art in this area.

An Ergonomic Study on Influence of Touch-screen Phone Size on Single-hand Operation Performance

Touch-screen smart phones have gradually occupied the market of traditional Qwerty Phones and become the mainstream products of mobile phone industry. However, few ergonomics research has been conducted on the touch screens of smart phones, while it has led to tendosynovitis among users owing to the overuse of thumbs. Sizes of smart phones in market range from 3.0 to 7.0 inches. What’s more, 4.0 inches and above are the common size of current touch screens. Also, considering the users’ habits, one-hand operation is preferred when the other hand is occupied. This paper has collected hand parameters of 80 subjects and has adopted an experiment which includes the performance testing and surveys of subjective evaluation by means of usability evaluation. After analysing correlation between touch-screen sizes and operation performances, the result indicates that under one-hand operation, the size of touch screen affects the operation performance significantly. However, it’s hard to implement one-hand operation if the touch-screen size is over 5.7 inches. Additionally, the thickness of smart phones affects the degree of comfort remarkably.

The rise of keyloggers on smartphones: A survey and insight into motion-based tap inference attacks

Smartphone sensing capabilities have opened new opportunities for innovative User Interface (UI) and context-aware applications. They have also opened new possibilities for potential risks to user privacy and security infiltration. Researchers have recently explored a new attack vector that exploits the built-in motion sensors to infer user taps on smartphone touchscreens. This new side channel has introduced the threat of keylogging to smartphones despite the lack of physical keyboards. In this paper, we review this type of attack and survey the leading works in the literature to highlight the underpinning motivations and threat model. We also discuss the main issues in the design and implementation of the new attack, in order to provide insights into the practicality, prospects, and limitations of the different approaches. Different countermeasures that can mitigate the rising threat are investigated, and recommendations for further research on this emerging trend are discussed. A comparative summary of the surveyed works is also presented.