Smartphone Measurements Research Articles

Daytime and nighttime smartphone use: A study of associations between multidimensional smartphone behaviours and sleep among 24,856 Danish adults.

The around-the-clock smartphone use and its relation to disturbed sleep is a public health concern. The present study aimed to quantify the effects of different dimensions of smartphone behaviours (frequency of daytime use, problematic use, use before sleep and use during the sleep period) on disturbed sleep (sleep quality and sleep quantity) and to disentangle their inter-relationship in a large population-based sample of 24,856 Danish adults aged ≥16years. Data come from the SmartSleep Experiment, which is a web-based survey carried out using a citizen science approach. Tested items were used to evaluate smartphone use and disturbed sleep was evaluated with the Karolinska Sleep Questionnaire (KSQ). Linear and multinomial logistic regression was employed to evaluate the relationship between smartphone use and disturbed sleep. While several of the smartphone measures were associated with disturbed sleep when assessed individually, smartphone use during the sleep period was the only dimension consistently associated with disturbed sleep when assessed independently of other smartphone behaviours. Weekly smartphone use during the sleep period versus no use was associated on average with a 0.96point higher score (95% confidence interval [CI] 0.90-1.02) on the 5-point KSQ scale, and a higher risk of both short (odds ratio [OR] 1.32, 95% CI 1.08-1.62) and long (OR 1.94, 95% CI 1.63-2.32) sleep duration. Smartphone use during the sleep period is the factor strongest associated to disturbed sleep relative to other dimensions of smartphone use. Recommendations around smartphone use during the sleep period are warranted in order to protect the fundamentally important biological and mental processes of sleep.

Conditioning and PPP processing of smartphone GNSS measurements in realistic environments

Smartphones typically compute position using duty-cycled Global Navigation Satellite System (GNSS) L1 code measurements and Single Point Positioning (SPP) processing with the aid of cellular and other measurements. This internal positioning solution has an accuracy of several tens to hundreds of meters in realistic environments (handheld, vehicle dashboard, suburban, urban forested, etc.). With the advent of multi-constellation, dual-frequency GNSS chips in smartphones, along with the ability to extract raw code and carrier-phase measurements, it is possible to use Precise Point Positioning (PPP) to improve positioning without any additional equipment. This research analyses GNSS measurement quality parameters from a Xiaomi MI 8 dual-frequency smartphone in varied, realistic environments. In such environments, the system suffers from frequent phase loss-of-lock leading to data gaps. The smartphone measurements have low and irregular carrier-to-noise (C/N0) density ratio and high multipath, which leads to poor or no positioning solution. These problems are addressed by implementing a prediction technique for data gaps and a C/N0-based stochastic model for assigning realistic a priori weights to the observables in the PPP processing engine. Using these conditioning techniques, there is a 64% decrease in the horizontal positioning Root Mean Square (RMS) error and 100% positioning solution availability in sub-urban environments tested. The horizontal and 3D RMS were 20 cm and 30 cm respectively in a static open-sky environment and the horizontal RMS for the realistic kinematic scenario was 7 m with the phone on the dashboard of the car, using the SwiftNav Piksi Real-Time Kinematic (RTK) solution as reference. The PPP solution, computed using the YorkU PPP engine, also had a 5–10% percentage point more availability than the RTK solution, computed using RTKLIB software, since missing measurements in the logged file cause epoch rejection and a non-continuous solution, a problem which is solved by prediction for the PPP solution. The internal unaided positioning solution of the phone obtained from the logged NMEA (The National Marine Electronics Association) file was computed using point positioning with the aid of measurements from internal sensors. The PPP solution was 80% more accurate than the internal solution which had periodic drifts due to non-continuous computation of solution.

Smartphone-Based Prediction Model for Postoperative Cardiac Surgery Outcomes Using Preoperative Gait and Posture Measures.

Gait speed assessment increases the predictive value of mortality and morbidity following older adults’ cardiac surgery. The purpose of this study was to improve clinical assessment and prediction of mortality and morbidity among older patients undergoing cardiac surgery through the identification of the relationships between preoperative gait and postural stability characteristics utilizing a noninvasive-wearable mobile phone device and postoperative cardiac surgical outcomes. This research was a prospective study of ambulatory patients aged over 70 years undergoing non-emergent cardiac surgery. Sixteen older adults with cardiovascular disease (Age 76.1 ± 3.6 years) scheduled for cardiac surgery within the next 24 h were recruited for this study. As per the Society of Thoracic Surgeons (STS) recommendation guidelines, eight of the cardiovascular disease (CVD) patients were classified as frail (prone to adverse outcomes with gait speed ≤0.833 m/s) and the remaining eight patients as non-frail (gait speed >0.833 m/s). Treating physicians and patients were blinded to gait and posture assessment results not to influence the decision to proceed with surgery or postoperative management. Follow-ups regarding patient outcomes were continued until patients were discharged or transferred from the hospital, at which time data regarding outcomes were extracted from the records. In the preoperative setting, patients performed the 5-m walk and stand still for 30 s in the clinic while wearing a mobile phone with a customized app “Lockhart Monitor” available at iOS App Store. Systematic evaluations of different gait and posture measures identified a subset of smartphone measures most sensitive to differences in two groups (frail versus non-frail) with adverse postoperative outcomes (morbidity/mortality). A regression model based on these smartphone measures tested positive on five CVD patients. Thus, clinical settings can readily utilize mobile technology, and the proposed regression model can predict adverse postoperative outcomes such as morbidity or mortality events.

Supporting operational site‐specific fertilization in rice cropping systems with infield smartphone measurements and Sentinel-2 observations

Due to the low efficiency of nitrogen fertilizers in flooded rice paddies, there is a rising demand for tools able to detect crop nitrogen status in space and time to allow farmers to use the technical novelties of precision agriculture to improve fertilizer management in extensive fields. This work sets up an operational approach to increase nitrogen use efficiency of top-dressing fertilization by supporting variable rate fertilization in rice cropping systems. The procedure exploits (i) crop modelling to identify best periods for fertilization (When), (ii) Sentinel-2 imagery to draw management zones (MZ) and lead field scouting (Where), and (iii) smartphone app to measure nitrogen nutritional index (NNI) (How much). Automatically generated MZ from Sentinel-2 data were able to identify within field patches with different nutritional status and NNI data well described the crop temporal dynamic in relation to crop development and nutritional needs. The workflow was implemented to provide farmers with timely information on plant nutritional status during the 2018 growing season to define site-specific fertilization strategies implemented with variable rate technology (VRT). Tests conducted on 6 fields over 30 ha in 3 farms showed the feasibility of the proposed workflow in real farming conditions allowing a reduction of applied fertilizer up to 25% in the areas with sufficient nutritional status. Demonstration revealed that VRT based on geospatial information from integrated in-field and satellite data can provide agronomic and environmental benefits compared with standard fertilization resulting in promising outcomes both in terms of yield (increase in the range 0.2–0.5 t ha−1) and nitrogen use efficiency (increase up to 7.8%).

Estimation of photocatalytic degradation rate using smartphone based analysis

A simple approach to test photocatalyst activity has been described. Photocatalytic degradation of a model dye was measured using a smartphone. The color changes were registered directly in the micro-photoreactor. The model dye Rhodamine B was degraded under UV irradiation (365 nm). The effect of H2O2 concentration and titanium dioxide photocatalyst dosage has been studied. Among three color systems, RGB, CIE L*a*b* and HSV, the first one proved to be the most suitable for the dye determination. The reference measurements were carried out with a UV-Vis spectrophotometer. Two smartphones and two tablets with different camera resolutions have been examined. The best calibration curve was obtained using a Samsung Galaxy A6 smartphone with a 16MP camera. The t-test has shown with 95 % confidence that there are no significant differences between the dye concentrations measured with the smartphone and spectrophotometer. The values of the relative standard deviation of the smartphone measurements were less than 0.5 %. Therefore, the proposed method for fast estimation of photocatalyst activity can be used in the control of advanced oxidation reactions.

Remote cognitive assessment approaches in the Dominantly Inherited Alzheimer Network (DIAN)

AbstractBackgroundThe “one‐shot” paradigm used in traditional in‐clinic cognitive assessments often produces unreliable data due to daily fluctuations in stress, sleep, test anxiety, and fatigue. In DIAN, an international study of familial Alzheimer’s disease (AD), these difficulties are compounded by the scarcity and younger age of the population. We have developed two assessment strategies to address these issues, which we are also validating in the Knight ADRC cohort. The first is a smartphone‐based cognitive assessment platform based on principles from ecological momentary assessment that uses frequent but extremely short (<60 seconds) tests of episodic memory, attentional control, and processing speed administered at random times over 7 days. We examine average performance and variability metrics across 7 days of assessments. The second is a web‐based assessment that focuses on repeated daily administration to measure long‐term memory decay and also skill acquisition learning. The rates of forgetting and rates of learning become the outcome measures.MethodDigital assessments were completed on cognitively normal DIAN participants (n = 56 mutation carriers, n = 60 non‐carriers) and 120 mostly cognitively normal older adults from the Knight ADRC. Follow‐up evaluations were available for approximately 40 DIAN participants. Digital assessments were compared with standard in‐clinic cognitive tests and also with AD biomarkers including amyloid PET, cerebrospinal fluid (CSF) tau, tau PET, and structural MRI.ResultReliabilities of all remote cognitive measures ranged from 0.90‐0.98. All measures (Smartphone and web‐based) correlated with age (r’s 0.22‐0.69), indicating worse performance with increasing age. Correlations with standard in‐clinic measures ranged from 0.24‐0.77, suggesting that remote tests are valid measures of cognition. Test‐retest reliability from repeated smartphone assessments was exceptional for two smartphone measures (ICC’s = 0.89‐0.94). Critically, smartphone measures and web‐based measures demonstrated sensitivity to all AD biomarkers, including amyloid PET, tau PET, CSF tau, and structural MRI. We will present data on relationships with AD biomarkers and data on technical validation of smartphone cognitive measures and adherence strategies for remote studies.ConclusionRemote assessments that rely on short‐term but high frequency testing can be deployed worldwide in adults of all ages and demonstrate excellent reliability and validity compared to standard in‐clinic cognitive assessments.

Smartphone measurements of physical activity and fitness are associated with early trial discontinuation of patients in (hemato)oncology phase I/II clinical trials

BackgroundPatients, who discontinue early, do not benefit from phase I/II clinical trials (early-phase clinical trials (EPCT)). In this study, associations between objective smartphone measurements of physical activity and fitness and early trial discontinuation in patients with cancer participating in EPCT were investigated.MethodsBefore start of treatment, physical activity (steps/day) and physical fitness (meters walked in 6 min) were measured with a smartphone, and patient-reported physical function (PRO-PF) was assessed (EORTC QLQ-C30-PF). Early trial discontinuation was defined as discontinuation ≤ 28 days. Univariable logistic regression analyses were performed to study associations of physical activity, fitness, and function with early trial discontinuation. Optimal cutoff values of physical activity and fitness were assessed with ROCs, based on positive predictive values (PPV).ResultsMedian (interquartile range (IQR)) step count was 4263 (2548–6897) steps/day, mean ± standard deviation 6-min walking distance was 477 ± 120 m and median (IQR) PRO-PF score was 83 (67–95) points. Fourteen patients (12%) discontinued the trial early. Smartphone measurements of physical activity in units of 100 steps per day (odds ratio (OR) = 0.96, 95% CI = 0.94–0.99, p = 0.01), physical fitness (OR = 0.99, 95% CI = 0.98–0.99, p < 0.01), and PRO-PF (OR = 0.97, 95% CI = 0.94–1.00, p = 0.03) were associated with early trial discontinuation. Optimal cutoff values were < 900 steps for physical activity and < 285 m for physical fitness. PPV for early trial discontinuation was 100% in patients who walked both < 1500 steps per day and < 300 m in 6 min.ConclusionsObjective smartphone measurements of physical activity and fitness are associated with early trial discontinuation. However, cutoff values should be externally validated in a larger cohort before implementation in clinical practice.

Validation of a smartphone embedded inertial measurement unit for measuring postural stability in older adults

BackgroundIdentifying older adults with increased fall risk due to poor postural control on a large scale is only possible through omnipresent and low cost measuring devices such as the inertial measurement units (IMU) embedded in smartphones. However, the correlation between smartphone measures of postural stability and state-of-the-art force plate measures has never been assessed in a large sample allowing us to take into account age as a covariate. Research questionHow reliably can postural stability be measured with a smartphone embedded IMU in comparison to a force plate? MethodsWe assessed balance in 97 adults aged 50–90 years in four different conditions (eyes open, eyes closed, semi-tandem and dual-task) in the anterio-posterior and medio-lateral directions. We used six different parameters (root mean square and average absolute value of COP displacement, velocity and acceleration) for the force plate and two different parameters (root mean square and average absolute value of COM acceleration) for the smartphone. ResultsTest-retest reliability was smaller for the smartphone than for the force plate (intra class correlation) but both devices could equally well detect differences between conditions (similar Cohen’s d). Parameters from the smartphone and the force plate, with age regressed out, were moderately correlated (robust correlation coefficients of around 0.5). SignificanceThis study comprehensively documents test-retest reliability and effect sizes for stability measures obtained with a force plate and smartphone as well as correlations between force plate and smartphone measures based on a large sample of older adults. Our large sample size allowed us to reliably determine the strength of the correlations between force plate and smartphone measures. The most important practical implication of our results is that more repetitions or longer trials are required when using a smartphone instead of a force plate to assess balance.

Reliability and Validity of Knee Joint Angles of the Elderly Measured Using Smartphones

Background: With the increasing elderly population, the need for gait analysis of these elderly individuals is also increasing. Most devices are costly and not portable; however, smartphones using built-in sensors capable of measuring motion and are easily available. Objectives: To examine the reliability and validity of knee joint angles of the elderly using smartphone measurements during walking. Design: Quasi-experimental research. Methods: Sixteen elderly people, aged 65+ and living in Daejeon and Chungbuk, South Korea, participated in the study. Electrogoniometers and smartphones were attached to the thigh and the side and front of the shank of each subject, respectively, using double-sided tape, an arm band, and an elastic band. Each subject completed two sets of at least seven gait cycles (14 steps). Results: Both the smartphones and electrogoniometers exhibited high agreement in terms of their primary and secondary measurements (ICC>.75). The agreement between the smartphones and electrogoniometers was also high in terms of both the primary and secondary measurements (ICC<.60). Conclusion: These results indicate that smartphones can be costly equipment cannot, even though they cannot completely replace existing clinical-grade devices. Their utility is emphasized herein for measuring knee joint angles of the elderly during walking.

Aiming for Cure and Preventive Initiatives in Psoriatic Disease: Building Synergy at NPF, GRAPPA, and PPACMAN.

To provide a general overview of the organizations dedicated to advance clinical and translational research in the field of psoriatic disease and to describe the current and future opportunities for team science approaches to overcome unmet needs in the field. Descriptions of initiatives from the NPF, PPACMAN, and GRAPPA are summarized. Program projects have recently identified areas of knowledge gaps in diagnosis, treatment, and prevention of psoriasis and psoriatic arthritis (PsA). NPF's Psoriasis Prevention Initiative aims to identify interventions that can prevent the onset and relapse of psoriatic disease or related comorbidities. The Psorcast Study is a joint venture between PPACMAN and Sage Bionetworks based on patient-generated smartphone measurements of psoriatic disease. Similarly, GRAPPA is involved in a number of projects related to axial PsA, enthesitis prevalence, and biomarker discoveries. As important initiatives bring new targets for diagnosis and therapeutics in psoriatic disease, supra-endeavors such as the NIH-Accelerating Medicines Partnership (AMP) and the European Innovative Medicines Initiative (IMI) are promising public-private partnerships that can significantly catapult the field forward.

Estimation of Wind Speed and Roughness Length Using Smartphones: Method and Quality Assessment

AbstractCrowdsourced data are now seen as a potential source of high-resolution observations in the atmospheric sciences. In this paper we investigate a potential data source, wind observations obtained using anemometers connected to handheld smartphones. The aim of this paper is twofold: to assess the quality of raw and height-extrapolated wind measurements from the handheld anemometer against professional-grade surface synoptic observation (SYNOP) stations, and to use these data of opportunity to infer a more accurate estimation of terrain roughness lengths. Roughness lengths are essential in numerical weather prediction; however, they are often poorly determined. Roughness lengths are also necessary when correcting near-surface wind observations for height offsets. For the analysis we performed a series of field experiments measuring wind profiles using handheld anemometers at roughly 2 m above ground. These raw measurements were then extrapolated to 10-m height using roughness lengths from three different sources. The extrapolation enabled us to compare the quality of roughness lengths estimated from smartphone measurements with those from traditional sources, as well as to assess the quality of these wind measurements against the professional-grade stations. We find that the handheld wind measurements are comparable in quality to wind measurements from SYNOP stations at 10-m height and that for some cases the handheld measurements can be more representative than SYNOP stations only about a kilometer away. To determine the roughness lengths, we examine a method that is based on the turbulent intensity derived from the high-frequency signal of the smartphone wind measurements. Under certain circumstances, the roughness lengths obtained with the approach presented here are superior to traditional sources.

In-Home Rehabilitation Using a Smartphone App Coupled With 3D Printed Functional Objects: Single-Subject Design Study.

BackgroundStroke is a major cause of long-term disability. While there is potential for improvements long after stroke onset, there is little to support functional recovery across the lifespan. mHealth solutions can help fill this gap. mRehab was designed to guide individuals with stroke through a home program and provide performance feedback.ObjectiveTo examine if individuals with chronic stroke can use mRehab at home to improve upper limb mobility. The secondary objective was to examine if changes in limb mobility transferred to standardized clinical assessments.MethodsmRehab consists of a smartphone coupled with 3D printed household items: mug, bowl, key, and doorknob. The smartphone custom app guides task-oriented activities and measures both time to complete an activity and quality of movement (smoothness/accuracy). It also provides performance-based feedback to aid the user in self-monitoring their performance. Task-oriented activities were categorized as (1) object transportation, (2) prehensile grip with supination/pronation, (3) fractionated finger movement, and (4) walking with object. A total of 18 individuals with stroke enrolled in the single-subject experimental design study consisting of pretesting, a 6-week mRehab home program, and posttesting. Pre- and posttesting included both in-laboratory clinical assessments and in-home mRehab recorded samples of task performance. During the home program, mRehab recorded performance data. A System Usability Scale assessed user’s perception of mRehab.ResultsA total of 16 participants completed the study and their data are presented in the results. The average days of exercise for each mRehab activity ranged from 15.93 to 21.19 days. This level of adherence was sufficient for improvements in time (t15=2.555, P=.02) and smoothness (t15=3.483, P=.003) in object transportation. Clinical assessments indicated improvements in functional performance (t15=2.675, P=.02) and hand dexterity (t15=2.629, P=.02). Participant’s perception of mRehab was positive.ConclusionsDespite heterogeneity in participants’ use of mRehab, there were improvements in upper limb mobility. Smartphone-based portable technology can support home rehabilitation programs in chronic conditions such as stroke. The ability to record performance data from home rehabilitation offers new insights into the impact of home programs on outcomes.Trial RegistrationClinicalTrials.gov NCT04363944; https://clinicaltrials.gov/ct2/show/NCT04363944

A systematic literature review of the factors affecting smartphone user threat avoidance behaviour

PurposeThere is a need for behavioural research within the smartphone context to better understand users’ behaviour, as it is one of the reasons for the proliferation of mobile threats. This study aims to identify the human factors that affect smartphone users’ threat avoidance behaviour.Design/methodology/approachA structured literature review (SLR) was applied to answer the research question. A total of 27 sources were analysed, from which 16 codes emerged. After synthesis, six themes transpired.FindingsSix factors were identified as drivers and/or challenges of smartphone users’ threat avoidance behaviour, namely, knowledge and awareness, misconceptions and trust, cost and benefit considerations, carelessness, perceived measure effectiveness and the user’s perceived skills and efficacy.Research limitations/implicationsThe results can encourage and provide a starting point for further research on human behaviour to improve smartphone user behaviour.Practical implicationsThe mobile industry should focus on eradicating common misconceptions and undue trust in mobile security that is prevalent among smartphone users and make cost effective and usable interventions available. Training and awareness programs should be updated to include the factors that were identified in this study to affect smartphone users’ threat avoidance behaviour. In addition to improving users’ declarative knowledge concerning available smartphone measures and tools, procedural knowledge should also be improved to ensure proper use of available protective measures. Users should realise the importance of staying updated with evolving smartphone technology and associated threats.Originality/valueThis study acknowledges and supports the notion that addressing human behaviour is crucial in the fight against mobile threats. It addresses the need for behavioural research to analyse the factors that drive smartphone user behaviour. Furthermore, it uses and documents the use of a SLR, a research technique often unfamiliar among information security researchers.

A smartphone-based quantitative point-of-care testing (POCT) system for simultaneous detection of multiple heavy metal ions

It is of great significance to develop versatile and cost-effective point-of-care testing (POCT) systems for simultaneous quantitation of multiple analytes on-site. This work reports on: 1) the customized electrodes which exhibit good analytical performance for simultaneous detection of Cd2+, Cu2+, Hg2+, Pb2+ with low detection limits (Cd2+, 0.296 μM; Cu2+, 0.055 μM; Hg2+, 0.351 μM; and Pb2+, 0.025 μM) and wide dynamic ranges (Cd2+, 0.50–12.5 μM; Cu2+, 0.10–9.50 μM; Hg2+, 0.50–12.5 μM; and Pb2+, 0.10–12.5 μM) using differential pulse voltammetry (DPV) measurements. 2) a hand-held electrochemical analyzer which can realize two-way communication with a smartphone and implement DPV measurements; its cost, weight and power consumption are ~$10.0, ~30 g and ~ 253 mW, respectively; 3) a self-developed APP DHMI which can control the analyzer, receive data from the analyzer, and plot the voltammograms on smartphone’s screen in real-time. This quantitative POCT system has been successfully demonstrated for simultaneous quantitation of Cd2+, Cu2+, Hg2+, Pb2+ in tap water, mineral water and Pearl River water, and the quantitation results correlated well with ICP-MS measurements. The features of cost-effectiveness, ease-to-use and reliability make this quantitative POCT system useful for on-site monitoring of multiple heavy metal ions, especially in resource-constrained environments.

Smartphone based meat freshness detection

In this work, a freshness colorimetric sensor has been integrated with pork meat packages. The sensor tracks rising CO2 levels in the package associated with meat spoilage, as CO2 levels increase with bacterial population. The color of the sensor changes depending on the quantity of bacteria present, therefore it can be correlated with the freshness of meat, in this case pork loin. Detection is achieved by a simple photograph using a smartphone, and analyzing the grey scale from the RGB space color with a custom made app. Only 2 μL of the cocktail (all components are nontoxic) is needed to prepare the sensor, which have been integrated inside meat packages using a variety of support materials prior to sealing. The Smartphone measurements have been validated using a reference method (Checkpoint Analyzer) and the results suggest it can provide the basis for a quick test of the quality of the packaged pork.

Wrist ROM measurements using smartphone photography: Reliability and validity

No one has validated measuring the wrist's active range of motion (ROM) using smartphone images in patients. It is not known whether pathological factors affect the accuracy of this measurement technique. The purpose of this study was to assess if smartphone photography is as reliable and valid as manual goniometry for measuring wrist joint ROM. We reviewed 38 wrists in 38 patients (21 women and 17 men) with a mean age of 45 years (range, 26–60). Smartphones were used to take digital photos of injured wrists at extremes of wrist motion, including flexion, extension, radial and ulnar deviation. The mean difference in measured ROM between the two measurement methods (digital photos and handheld goniometer) was compared using Student's t test and the relationship determined using Pearson correlation coefficients. Bland-Altman analysis was used to define the limits of agreement (LOA). No significant difference was found when comparing the wrist ROM in the four positions using manual goniometry and digital measurements from photos taken by a surgeon. Between the goniometer measurements and digital photos taken by a surgeon, the Pearson coefficients were high, with most being above 0.8 for the four positions. The Pearson coefficients also show the smartphone measurements were highly precise. There was high reliability between the photographs taken by surgeons and by patients, as well as high interobserver reliability. Smartphone photography is a reliable and valid method to measure wrist joint ROM in patients. This measurement method can be used to measure outcomes.

Influence of hand and smartphone anthropometric measurements on hand pain and discomfort: A cross-sectional study.

A good mobile phone design may increase the productivity of users, as well as their comfort. To achieve mobile users’ satisfaction, there is a need to come up with an ideal measurement that would not strain the human's body parts used to control the devices.To investigate the correlation between smartphone and hand anthropometry measurements and the development of hand discomfort and pain.89 Ahlia University students between the ages of 17- and 30-year-old participated in this study. Participants completed a demographic data sheet and had both of their hand dimensions and grip strength measured.A total number of 89 participants were recruited in this study with (57.3%) females and (42.7%) males. 38% have had hand pain recently while 61.8% did not experience any hand pain. There was weak negative correlation between the phone size (r = −0.04, P = .7), hand size (r = −0.08, P = .5), and the hand grip strength (r = −0.03, P = .7) all with the reporting of hand pain. For the phone screen size and the hand lengths (r = 0.22, P = .13) there was weak positive correlation.Mobile phone manufacturers should take into account the users’ comfort when designing their phones as this could lead to hand pain and other musculoskeletal problems. Furthermore, hand pain is multifactorial so hand size; phone size and grip strength may be taken into account.

INFORMATION TECHNOLOGY USAGE: QUANTITATIVE ANALYSIS OF SMARTPHONE SECURITY AWARENESS AND PRACTICES AMONG UNDERGRADUATE STUDENTS IN THE UNITED STATES

Mobile phone usage is growing at an unprecedented rate. The ability to remain connected, the ease of smart phone use and declining mobile costs have allowed this technology to expand at a very high rate globally. The study aimed to quantitatively determine the reasons for inactive practice of security measures of smart-phone usage among college students in the United States. The study also examined the Consideration of Future Consequences (CFC) level in relation to the level of smart-phone security measures, determined the levels of security measures on smart-phone (SP) by users, and establish the relationship between CFC level and the levels of smart-phone security measures among college students. Using a quantitative research survey and simple random sampling procedure, the methodology focused on analyzing data through testing of hypotheses. The t-test, Pearson’s correlation, regression coefficients and their respective p-values. The results showed 69.8% of college students set PIN, password and screen lock on their smart phones while 74.8% were cautious with smart phone applications and 6.2% practiced on setting of security software including rooting services. On the other hand, 35.4% protected their SP data through encryption, 47.4% had data checks and security alert while 46.2% had set Bluetooth applications and 41.4% had used backup storage for sensitive data. Use of Biometrics or other security unknown security adoptions were not included in the study. The study also found that lack of knowledge about technology or applications for SP security, lack of security habits and practices, rigorous involvement of setting SP security details like backups, encryption, security software etc., assumptions that SP are security and tamper-proof as well as lack of training, guidance and after sale services on SP security are significant reasons for lack of security measures practices concerning smart-phone usage by college students.

Roughness-induced vehicle energy dissipation from crowdsourced smartphone measurements through random vibration theory

Abstract We propose, calibrate, and validate a crowdsourced approach for estimating power spectral density (PSD) of road roughness based on an inverse analysis of vertical acceleration measured by a smartphone mounted in an unknown position in a vehicle. Built upon random vibration analysis of a half-car mechanistic model of roughness-induced pavement–vehicle interaction, the inverse analysis employs an L2 norm regularization to estimate ride quality metrics, such as the widely used International Roughness Index, from the acceleration PSD. Evoking the fluctuation–dissipation theorem of statistical physics, the inverse framework estimates the half-car dynamic vehicle properties and related excess fuel consumption. The method is validated against (a) laser-measured road roughness data for both inner city and highway road conditions and (b) road roughness data for the state of California. We also show that the phone position in the vehicle only marginally affects road roughness predictions, an important condition for crowdsourced capabilities of the proposed approach.

Investigation of collision warning possibilities by means of GNSS receivers of Android smartphones

Using of raw GNSS measurements in Andoid smartphones for precise mututal positioning of vehicles on a road is considered in the Paper. Field experiments with two moving vehicles and pedestrian were conducted. 15 kinds of general maneuvers were provided (overtaking, turn, oncoming traffic, etc.). Smartphone measurements were logged and post-processed to get mutual positioning estimations during maneuvering. Smartphone estimations were compared with precision GNSS receivers measurements.