Smartphone-based wearable microfluidic electrochemical sensor for on-site monitoring of copper ions in sweat without external driving.

The directional movement of liquid without exogenous drive can show great potential in portable electrochemical platforms. Herein, we developed a portable electrochemical platform that drove electrolyte flow by surface tension gradient, which can realize collection of electrolyte, flow preconcentration and electrochemical detection of Cu2+. The induced graphene electrodes (LIG) was fabricated using laser direct writing, and flower cluster shaped ZnO nanorods (FC-ZnONRs) were prepared and modified on LIG, which provided a large amount of space for electrolyte to shuttled between the holes of LIG and ZnO, and increased the electrochemical active sites and electrons transport ability. The effect of surface tension gradients driving fluid flow could accelerate preconcentration, shorten detection time (save 300 s of preconcentration time) and enhance electrochemical responses in synergy with the 3D FC-ZnONRs/LIG. The microfluidic system possessed excellent performance for detection of Cu2+ ranged from 1 µg L-1 to 2100 µg L-1 with a low detection limit (LOD) of 0.0368 µg L-1 and high sensitivity of 0.414 µA (µg L-1)-1 cm-2. Additionally, this portable microfluidic system was successfully worn on the skin for analysing Cu2+ in human sweat, and the results showed good consistency with inductively coupled plasma-mass spectrometry (ICP-MS). This novel sensing system provides a sample collection, rapid detection, low cost and easy-to-operate strategy for heavy metal ions analysis in real samples and shows huge application prospects in point-of-care testing.

On-site colorimetric food spoilage monitoring with smartphone embedded machine learning.

Real-time and on-site food spoilage monitoring is still a challenging issue to prevent food poisoning. At the onset of food spoilage, microbial and enzymatic activities lead to the formation of volatile amines. Monitoring of these amines with conventional methods requires sophisticated, costly, labor-intensive, and time consuming analysis. Here, anthocyanins rich red cabbage extract (ARCE) based colorimetric sensing system was developed with the incorporation of embedded machine learning in a smartphone application for real-time food spoilage monitoring. FG-UV-CD100 films were first fabricated by crosslinking ARCE-doped fish gelatin (FG) with carbon dots (CDs) under UV light. The color change of FG-UV-CD100 films with varying ammonia vapor concentrations was captured in different light sources with smartphones of various brands, and a comprehensive dataset was created to train machine learning (ML) classifiers to be robust and adaptable to ambient conditions, resulting in 98.8% classification accuracy. Meanwhile, the ML classifier was embedded into our Android application, SmartFood++, enabling analysis in about 0.1 s without internet access, unlike its counterpart using cloud operation via internet. The proposed system was also tested on a real fish sample with 99.6% accuracy, demonstrating that it has a great advantage as a potent tool for on-site real-time monitoring of food spoilage by non-specialized personnel.

Fluorescent and smartphone imaging detection of tetracycline residues based on luminescent europium ion-functionalized the regular octahedral UiO-66-NH2.

Antibiotic residues cause extensive damage to food security, thus arousing serious concerns. Hence, rapid and sensitive detection of antibiotic residues is crucial to food safety. This study aimed to propose a portable, visual, intelligent and rapid method for tetracycline detection. We developed a ratiometric fluorescent sensor based on the Eu3+-functionalized regular octahedral UiO-66-NH2 material. The developed sensor could quantify tetracycline in the concentration range of 0.5-200 µM with a detection limit as low as 0.2 µM under the optimum conditions. Furthermore, the analytical results obtained using the designed sensor in the actual samples were basically consistent with those obtained using high-performance liquid chromatography. Based on these achievements, a smartphone application-integrated fluorescent testing paper was designed for facile, intelligent, and visual detection of tetracycline. The integrated portable sensor not only saved cost and time for testing but also provided a forward-looking approach to fast, sensitive detection of antibiotic residues.

A portable multi-channel fluorescent paper-based microfluidic chip based on smartphone imaging for simultaneous detection of four heavy metals.

Due to the excessive contamination of heavy metals pollution, it is very urgent and necessary to develop a real-time detection method for the heavy metals in food. As a target sensing device, a paper-based microfluidic device (µPAD) has the advantages of simplicity, low-cost, and portability. In this study, a self-driven microfluidic paper-based chip was first developed for the simultaneous detection of four targets. The channels on the microfluidic chip were prepared by using wax printing and automatic screen printing on the filter paper, where liquid flowed by capillary force without pump assistance. Based on the specific binding ability of aptamers to heavy metals, a "turn-on" fluorescence aptasensor for the simultaneous detection of four heavy metal ions was developed on the proposed multi-channel device via smartphone imaging. The obtained fluorescence images were digitized into RGB color values by Image J software, and an M-mode was established to realize the quantitative detection of heavy metal ions. Under optimal conditions, the limits of detection for lead(II), mercury(II), cadmium(II), and arsenic(III) were 4.20 nM, 1.70 nM, 2.04 nM, and 1.65 nM, respectively. Furthermore, the aptasensor was successfully applied to the quantitative detection of four heavy metal ions in apple and lettuce samples with recovery rates of 84.0%-104.1%.

On-site quantitation of xanthine in fish and serum using a smartphone-based spectrophotometer integrated with a dual-readout nanosensing assay.

Rapid and quantitative biochemical analysis at points-of-need is imperative for food safety inspection. This work reports on: 1) a stand-alone smartphone-based "two-in-one" spectrophotometer (the SAFS) installed with a self-developed application (the SAFS-App) which can precisely collect both absorption spectra and fluorescence spectra in a reproducible manner within 5 s; and 2) a straightforward protocol for xanthine detection using fluorescent carbon nanodots and silver nanoparticles. The assay performed with the SAFS demonstrates high specificity towards xanthine, and a linear range of 1-60 µM with LODs of 0.38 and 0.58 µM for colorimetric and fluorometric readouts, respectively. The reliability and robustness of the SAFS are validated by on-site quantitation of xanthine in fish and serum samples, with comparable accuracy to HPLC method. More importantly, the SAFS presents itself as an appealing device which is accessible to everyone through the Internet of Things and can be tailored for diverse point-of-care testing applications.

Smartphone-based electrochemical sensor for cost-effective, rapid and on site detection of chlorogenic acid in herbs using biomass-derived hierarchically porous carbon synthesized by a soft-hard dual template method.

To achieve excellent germplasm resource screening and ensure the quality control of herbal tea raw material, it is important to establish a cost-effective, rapid, and on site quantitative detection method for their bioactive constituents. We developed a smartphone-operated sensor for electrochemical detection of chlorogenic acid (CGA) using hierarchically porous carbon (DSiFPC), synthesized through a soft-hard dual template strategy with tannin acid as a carbon source, silica colloid as a hard template, and Pluronic F127 as a soft template. The DSiFPC modified glassy carbon electrode sensor showed excellent electrocatalytic ability towards CGA, with a wide linear range of 0.03-1 µM and a low limit of detection of 6.2 nM. It was successfully applied for detecting CGA in dried flowers of Lonicera japonica. Furthermore, a portable sensor utilizing a DSiFPC modified screen-printed electrode was employed for on site detection of CGA in fresh Eucommia ulmoides leaves, yielding satisfactory recoveries.

Rapid and sensitive point-of-need aflatoxin B1 testing in feedstuffs using a smartphone-powered mobile microfluidic lab-on-fiber device.

Rapid, high-frequency, and accurate identification of aflatoxin B1 (AFB1) is crucial for ensuring food safety and reducing population mortality. Herein, we constructed Smartphone powered Mobile mIcrofluidic Lab-on-fiber dEvice (SMILE) comprising a compact optical system, fiber nano-bioprobe-embedded microfluidic-chip system, mini-photodetector, and software application to facilitate the rapid and sensitive point-of-need quantitative testing for AFB1. The elegant optical design of SMILE significantly improves light transmission efficiency, detection sensitivity, and portability by integrating a compacted all-fiber optical structure with a fiber nano-bioprobe-embedded microfluidic chip. Furthermore, the nanopore layer of the fiber nano-bioprobe improves detection sensitivity by increasing the biorecognition molecule number and enhancing the interaction between the evanescent field and dye. Through an indirect competitive immunoassay mechanism, SMILE achieves sensitive quantitative detection of AFB1 with a detection limit of 0.08 µg/L. Herein, SMILE was validated using several feedstuff samples tested with a simple aqueous extraction protocol, demonstrating good correlation with high-performance liquid chromatography for AFB1-contaminated feedstuffs. The immunoassay process is completed within 12 min, boasting high sensitivity, specificity, reusability, and reproducibility. Owing to its sensitivity, portability, flexibility, plug-and-play, and smartphone integration, SMILE is highly scalable for rapid and high-frequency point-of-need testing for AFB1 and other trace contaminants.

Smartphone-Based High-Throughput Fluorimetric Assay for Histidine Quantification in Human Urine Using 96-Well Plates.

A high-throughput fluorimetric assay for histidine was developed, using a 96-well plates platform. The analyte reacts selectively with o-phthalaldehyde under mild alkaline conditions to form a stable derivative. Instrumental-free detection was carried out using a smartphone after illumination under UV light (365 nm). The method was proved to be linear up to 100 µM histidine, with an LLOQ (lower limit of quantification) of 10 µM. The assay was only prone to interference from glutathione and histamine that exist in the urine samples at levels that are orders of magnitude lower compared to histidine. Human urine samples were analyzed following minimum treatment and were found to contain histidine in the range of 280 to 1540 µM. The results were in good agreement with an HPLC corroborative method.

Monitoring Distracted Driving Behaviours with Smartphones: An Extended Systematic Literature Review.

Driver behaviour monitoring is a broad area of research, with a variety of methods and approaches. Distraction from the use of electronic devices, such as smartphones for texting or talking on the phone, is one of the leading causes of vehicle accidents. With the increasing number of sensors available in vehicles, there is an abundance of data available to monitor driver behaviour, but it has only been available to vehicle manufacturers and, to a limited extent, through proprietary solutions. Recently, research and practice have shifted the paradigm to the use of smartphones for driver monitoring and have fuelled efforts to support driving safety. This systematic review paper extends a preliminary, previously carried out author-centric literature review on smartphone-based driver monitoring approaches using snowballing search methods to illustrate the opportunities in using smartphones for driver distraction detection. Specifically, the paper reviews smartphone-based approaches to distracted driving behaviour detection, the smartphone sensors and detection methods applied, and the results obtained.

AMTASTM and user-operated smartphone research application audiometry-An evaluation study.

OBJECTIVE: To evaluate two user-operated audiometry methods, the AMTASTM PC-based audiometry and a low-cost smartphone audiometry research application (R-App). DESIGN: A repeated-measures within-subject study design was used to compare both user-operated methods to traditional manual audiometry and to evaluate test-retest reliability of each method. STUDY SAMPLE: 58 subjects were recruited in the study of which 83 ears had normal hearing thresholds and 33 ears had hearing loss (pure-tone average > 25 dB HL). Average age of participants was 44.8 years, with an age range of 11-85. RESULTS: Standard deviation of absolute differences ranged between 3.9-6.9 dB on AMTASTM and 4.5-6.8 dB on the R-App. The highest variability was found at the 8000 Hz frequency (R-App and AMTASTM test) and 3000 Hz frequency (AMTASTM retest). Evaluation of test-retest reliability of AMTASTM and R-App showed SD of absolute differences ranging between 3.5-5.8 dB and 3.1-5.0 dB, respectively. The mean threshold difference between test and retest was within ±1.5 dB on AMTASTM and ±1 dB on the R-App. CONCLUSION: Accuracy of AMTASTM and the R-App was within acceptable limits for audiometry and comparable to traditional manual audiometry on all tested frequencies (250-8000 Hz). Evaluation of test-retest reliability showed acceptable variation on both AMTASTM and R-App. Both user-operated methods could be reliably performed in a quiet non-soundproofed environment.

Determination of the cutoff point for Smartphone Application-Based Addiction Scale for adolescents: a latent profile analysis.

BACKGROUNDS: The Smartphone Application-Based Addiction Scale (SABAS) is a validated 6-item measurement tool for assessing problematic smartphone use (PSU). However, the absence of established cutoff points for SABAS hinders its utilities. This study aimed to determine the optimal cutoff point for SABAS through latent profile analysis (LPA) and receiver operating characteristic curve (ROC) analyses among 63, 205. Chinese adolescents. Additionally, the study explored whether PSU screening with SABAS could effectively capture problematic social media use (PSMU) and internet gaming disorder (IGD). METHOD: We recruited 63,205. adolescents using cluster sampling. Validated questionnaires were used to assess PSMU, IGD, and mental health (depression, anxiety, sleep disturbances, well-being, resilience, and externalizing and internalizing problems). RESULTS: LPA identified a 3-class model for PSU, including low-risk users (38.6%, n = 24,388.), middle-risk users (42.5%, n = 26,885.), and high-risk users (18.9%, n = 11,932.). High-risk users were regarded as "PSU cases" in ROC analysis, which demonstrated an optimal cut-off point of 23 (sensitivity: 98.1%, specificity: 96.8%). According to the cutoff point, 21.1% (n = 13,317.) were identified as PSU. PSU adolescents displayed higher PSMU, IGD, and worse mental health. PSU screening effectively captured IGD (sensitivity: 86.8%, specificity: 84.5%) and PSMU (sensitivity: 84.5%, specificity: 80.2%). CONCLUSION: A potential ideal threshold for utilizing SABAS to identify PSU could be 23 (out of 36). Employing SABAS as a screening tool for PSU holds the potential to reliably pinpoint both IGD and PSMU.

Smartphone-Assisted Medical Care for Vestibular Dysfunction as a Telehealth Strategy for Digital Therapy Beyond COVID-19: Scoping Review.

BACKGROUND: Dizziness and vertigo can be caused by various factors, such as peripheral vestibular and central disorders. Although consultations with specialists are advisable when necessary, patients with severe vertigo symptoms may have limited mobility, which may interfere with hospital visits. The spread of COVID-19 has further limited the number of hospital visits for patients with dizziness; therefore, a method of medical care that enables more accurate treatment under time and geographical constraints is needed. Telemedicine has become widespread, owing to the popularity of smartphone and tablet devices in recent years, and the use of devices and systems has made it possible to provide efficient medical care. However, no previous scoping review has mapped existing studies on telemedicine for vertigo and dizziness, and no recommendations have been made regarding which devices and systems should be used for specific diseases. OBJECTIVE: The aim of this review was to map and assess previous studies on the use of information communications technology, smartphones, and apps for treating patients with vertigo and discuss the added value of introducing telemedicine to improve the quality of medical care and create an environment that builds security and trust among patients. METHODS: A scoping review was conducted with the methodological framework of Arksey and O'Malley and in accordance with the of the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews) guidelines. The PubMed, MEDLINE, and Cochrane Library databases were searched to retrieve previous reports on smartphone-assisted telemedicine treatment for vertigo published between January 2000 and May 2023. Two authors independently assessed eligibility and extracted data. RESULTS: This review included 20 papers that reported devices or systems for telemedicine for vestibular dysfunction. Among studies that reported the use of a device or app, 2 were related to anamnesis and subjective symptoms, 12 were related to objective examination, 7 were related to remote diagnosis, and 7 were related to treatment and rehabilitation. CONCLUSIONS: With the advancement of technology, the use of telemedicine in patients with dizziness may be feasible. In the future, it will be necessary to consider how telemedicine can be used in dizziness treatment and develop an effective treatment system combining in-person medical care and the effective use of devices for the management of severe vertigo and related diseases. The smooth introduction of telemedicine in vertigo treatment is expected to improve the quality of treatment, increase opportunities for patients to receive medical care, and reduce time and travel costs, leading to a sense of security and trust among patients.

Prevalence of distracted driving by driver characteristics in the United States.

INTRODUCTION: Distracted driving is a long-standing traffic safety concern, though common secondary tasks continually evolve. The goal of this study was to measure the prevalence of self-reported distracted driving behaviors, including activities made possible in recent years by smartphones. METHODS: We conducted a nationwide survey of 2,013 U.S. licensed drivers (ages 16 +). We created four aggregate distraction categories from 18 individual secondary tasks to estimate the proportion of drivers study-wide and by demographic characteristics belonging to each category, defined as those who regularly did (during most or all drives in the previous 30 days) one or more secondary task within each category. Logistic regression estimated the adjusted odds of drivers belonging to each aggregate distraction category by demographic characteristics. RESULTS: Sixty-five percent of drivers reported doing at least one of the 18 secondary tasks regularly, and half did at least one device-based task regularly in the past 30 days. Non-device task prevalence trended downward with age, while device-based task prevalence was consistent among younger drivers before declining beginning with age 35. Males (OR, 1.53; 95% CI, 1.16, 2.02), parents of children ages 18 and younger (OR, 1.47; 95% CI, 1.10, 1.96), and participants who drive in the gig economy (OR, 3.85; 95% CI, 2.73, 5.43) had higher adjusted odds of engaging in "modern" device-based distractions enabled by smartphones (e.g., making video calls, watching videos, using social media) than other drivers. Many drivers are using hands-free capabilities when available for tasks, but for some tasks more than others. CONCLUSIONS: Regular distracted driving is widespread with most behavior concentrated among drivers younger than age 50, though no age group or other demographic studied abstains. PRACTICAL APPLICATIONS: Stakeholders can use these findings to develop countermeasures for distracted driving by targeting specific secondary tasks and the demographics most likely to report regularly doing them.

Self-template sacrifice and in situ oxidation of a constructed hollow MnO2 nanozymes for smartphone-assisted colorimetric detection of liver function biomarkers.

Liver function tests play a vital role in accurately diagnosing liver diseases, monitoring treatment outcomes, and assessing liver damage severity. Here, we introduce a novel approach to develop a smartphone-assisted portable colorimetric sensor for rapid detection of three liver function biomarkers: aspartate aminotransferase (AST), alanine aminotransferase (ALT), and alkaline phosphatase (ALP). This sensor is based on the inherent enzyme-like activities of hollow MnO2 (H-MnO2). The H-MnO2 is synthesized via a self-template sacrifice and in situ oxidation strategy, utilizing a manganese-based Prussian blue analogue (Mn-PBA) as a sacrificial template. The resulting H-MnO2 exhibits a polycrystalline structure with a large specific surface area. By encapsulating the H-MnO2 in sodium alginate, we construct a portable sensing platform facilitating specific and rapid colorimetric detection of the three liver function biomarkers with the assistance of a smartphone. The developed sensor demonstrates outstanding sensitivity and stability, achieving detection limits of 4.9 U L-1, 3.6 U L-1, and 0.99 U L-1 for AST, ALT, and ALP, respectively. Importantly, this work introduces an innovative in situ oxidation method for fabricating hollow nanozymes, offering a cost-effective and convenient assay for liver function biomarkers detection.

Blood Pressure Measurement Based on the Camera and Inertial Measurement Unit of a Smartphone: Instrument Validation Study.

Background: Even though several mobile apps that can measure blood pressure have been developed, the data about the accuracy of these apps are limited. Objective: We assessed the accuracy of AlwaysBP (test) in blood pressure measurement compared with the standard, cuff-based, manual method of brachial blood pressure measurement (reference). Methods: AlwaysBP is a smartphone software that estimates systolic blood pressure (SBP) and diastolic blood pressure (DBP) based on pulse transit time (PTT). PTT was calculated with a finger photoplethysmogram and seismocardiogram using, respectively, the camera and inertial measurement unit sensor of a commercially available smartphone. After calculating PTT, SBP and DBP were estimated via the Bramwell-Hill and Moens-Korteweg equations. A calibration process was carried out 3 times for each participant to determine the input parameters of the equations. This study was conducted from March to August 2021 at Chungnam National University Sejong Hospital with 87 participants aged between 19 and 70 years who met specific conditions. The primary analysis aimed to evaluate the accuracy of the test method compared with the reference method for the entire study population. The secondary analysis was performed to confirm the stability of the test method for up to 4 weeks in 15 participants. At enrollment, gender, arm circumference, and blood pressure distribution were considered according to current guidelines. Results: Among the 87 study participants, 45 (52%) individuals were male, and the average age was 35.6 (SD 10.4) years. Hypertension was diagnosed in 14 (16%) participants before this study. The mean test and reference SBPs were 120.0 (SD 18.8) and 118.7 (SD 20.2) mm Hg, respectively (difference: mean 1.2, SD 7.1 mm Hg). The absolute differences between the test and reference SBPs were <5, <10, and <15 mm Hg in 57.5% (150/261), 84.3% (220/261 ), and 94.6% (247/261) of measurements. The mean test and reference DBPs were 80.1 (SD 12.6) and 81.1 (SD 14.4) mm Hg, respectively (difference: mean -1.0, SD 6.0 mm Hg). The absolute differences between the test and reference DBPs were <5, <10, and <15 mm Hg in 75.5% (197/261), 93.9% (245/261), and 97.3% (254/261) of measurements, respectively. The secondary analysis showed that after 4 weeks, the differences between SBP and DBP were 0.1 (SD 8.8) and -2.4 (SD 7.6) mm Hg, respectively. Conclusions: AlwaysBP exhibited acceptable accuracy in SBP and DBP measurement compared with the standard measurement method, according to the Association for the Advancement of Medical Instrumentation/European Society of Hypertension/International Organization for Standardization protocol criteria. However, further validation studies with a specific validation protocol designed for cuffless blood pressure measuring devices are required to assess clinical accuracy. This technology can be easily applied in everyday life and may improve the general population's awareness of hypertension, thus helping to control it.

A Novel Inexpensive Camera-Based Photoelectric Barrier System for Accurate Flying Sprint Time Measurement.

This paper introduces a novel approach to addressing the challenge of accurately timing short distance runs, a critical aspect in the assessment of athletic performance. Electronic photoelectric barriers, although recognized for their dependability and accuracy, have remained largely inaccessible to non-professional athletes and smaller sport clubs due to their high costs. A comprehensive review of existing timing systems reveals that claimed accuracies beyond 30 ms lack experimental validation across most available systems. To bridge this gap, a mobile, camera-based timing system is proposed, capitalizing on consumer-grade electronics and smartphones to provide an affordable and easily accessible alternative. By leveraging readily available hardware components, the construction of the proposed system is detailed, ensuring its cost-effectiveness and simplicity. Experiments involving track and field athletes demonstrate the proficiency of the proposed system in accurately timing short distance sprints. Comparative assessments against a professional photoelectric cells timing system reveal a remarkable accuracy of 62 ms, firmly establishing the reliability and effectiveness of the proposed system. This finding places the camera-based approach on par with existing commercial systems, thereby offering non-professional athletes and smaller sport clubs an affordable means to achieve accurate timing. In an effort to foster further research and development, open access to the device's schematics and software is provided. This accessibility encourages collaboration and innovation in the pursuit of enhanced performance assessment tools for athletes.

The STEPWISE study: study protocol for a smartphone-based exercise solution for people with Parkinson's Disease (randomized controlled trial).

BACKGROUND: Exercise has various health benefits for people with Parkinson's disease (PD). However, implementing exercise into daily life and long-term adherence remain challenging. To increase a sustainable engagement with physical activity of people with PD, interventions that are motivating, accessible, and scalable are needed. We primarily aim to investigate whether a smartphone app (STEPWISE app) can increase physical activity (i.e., step count) in people with PD over one year. Our second aim is to investigate the potential effects of the intervention on physical fitness, and motor- and non-motor function. Our third aim is to explore whether there is a dose-response relationship between volume of physical activity and our secondary endpoints. METHODS: STEPWISE is a double-blind, randomized controlled trial. We aim to include 452 Dutch people with PD who can walk independently (Hoehn & Yahr stages 1-3) and who do not take more than 7,000 steps per day prior to inclusion. Physical activity levels are measured as step counts on the participant's own smartphone and scaled as percentage of each participant's baseline. Participants are randomly assigned to an active control group with an increase of 5-20% (active controls) or any of the three intervention arms with increases of 25-100% (intermediate dose), 50-200% (large dose), or 100-400% (very large dose). The primary endpoint is change in step count as measured by the STEPWISE smartphone app from baseline to 52 weeks. For our primary aim, we will evaluate the between-group difference in average daily step count change from baseline to 52 weeks. For our second aim, measures of physical fitness, and motor- and non-motor function are included. For our third aim, we will associate 52-week changes in step count with 52-week changes in secondary outcomes. DISCUSSION: This trial evaluates the potential of a smartphone-based intervention to increase activity levels in people with PD. We envision that motivational apps will increase adherence to physical activity recommendations and could permit conduct of remote clinical trials of exercise for people with PD or those at risk of PD. TRIAL REGISTRATION: ClinicalTrials.gov; NCT04848077; 19/04/2021. CLINICALTRIALS: gov/ct2/show/NCT04848077.

Effect of day time on smartphone use posture and related musculoskeletal disorders risk: a survey among university students.

BACKGROUND: Musculoskeletal disorders (MSDs) are one of the most important problems among young smartphone users worldwide. Portability leads to a wide variety of postures during the different activities of the day. The objective evaluation of these postures coupled with ergonomic tools allows evaluating the level of MSD risk to which users are exposed. METHODS: The purpose was to investigate the effect of the time of day on the posture adopted during smartphone use among university students. The study was conducted through a cross-sectional survey of 263 university sports students. Four time of day, i.e. morning, afternoon, evening and night, and a taxonomy of 41 postures called SmarTaxo were considered. SmarTaxo included 18 sitting, 11 standing, 10 lying and 2 walking postures and their ergonomic score. After checking the normality of the data, a non-parametric Kruskal-Wallis test was used to study the effect of the time of day on the use duration of the different postures. RESULTS: The total mean duration use per typical weekday was 5.39 ± 2.19 h for males and 5.15 ± 1.60 h for females with maximal duration during evening. The average smartphone use durations were statistically longer in afternoon and evening for all sitting (9.44 and 9.22 min respectively, p < 0.05) and calling (3.38 and 3.33 min respectively, p < 0.05) postures. The longest duration for standing postures was recorded for afternoon (8.91 min, p < 0.05). The lying postures were significantly more present in evening (19.36 min). Some postures were more used during a time of day. The side-lying posture was used more in evening and has an ergonomic score of 6, i.e. a high MSD risk. CONCLUSIONS: The survey showed that users are exposed to MSDs regardless of posture and time of day. Sitting postures are used more in the morning and afternoon while lying postures are used more in the evening. As long as the rate of use is so high (> 5 h per day), young people will remain highly exposed to MSDs.

The effect of smartphone-based monitoring and treatment including clinical feedback versus smartphone-based monitoring without clinical feedback in bipolar disorder: the SmartBipolar trial-a study protocol for a randomized controlled parallel-group trial.

INTRODUCTION: A substantial proportion of patients with bipolar disorder experience daily subsyndromal mood swings, and the term "mood instability" reflecting the variability in mood seems associated with poor prognostic factors, including impaired functioning, and increased risk of hospitalization and relapse. During the last decade, we have developed and tested a smartphone-based system for monitoring bipolar disorder. The present SmartBipolar randomized controlled trial (RCT) aims to investigate whether (1) daily smartphone-based outpatient monitoring and treatment including clinical feedback versus (2) daily smartphone-based monitoring without clinical feedback or (3) daily smartphone-based mood monitoring only improves mood instability and other clinically relevant patient-related outcomes in patients with bipolar disorder. METHODS AND ANALYSIS: The SmartBipolar trial is a pragmatic randomized controlled parallel-group trial. Patients with bipolar disorder are invited to participate as part of their specialized outpatient treatment for patients with bipolar disorder in Mental Health Services in the Capital Region of Denmark. The included patients will be randomized to (1) daily smartphone-based monitoring and treatment including a clinical feedback loop (intervention group) or (2) daily smartphone-based monitoring without a clinical feedback loop (control group) or (3) daily smartphone-based mood monitoring only (control group). All patients receive specialized outpatient treatment for bipolar disorder in the Mental Health Services in the Capital Region of Denmark. The trial started in March 2021 and has currently included 150 patients. The outcomes are (1) mood instability (primary), (2) quality of life, self-rated depressive symptoms, self-rated manic symptoms, perceived stress, satisfaction with care, cumulated number and duration of psychiatric hospitalizations, and medication (secondary), and (3) smartphone-based measures per month of stress, anxiety, irritability, activity, and sleep as well as the percentage of days with presence of mixed mood, days with adherence to medication and adherence to smartphone-based self-monitoring. A total of 201 patients with bipolar disorder will be included in the SmartBipolar trial. ETHICS AND DISSEMINATION: The SmartBipolar trial is funded by the Capital Region of Denmark and the Independent Research Fund Denmark. Ethical approval has been obtained from the Regional Ethical Committee in The Capital Region of Denmark (H-19067248) as well as data permission (journal number: P-2019-809). The results will be published in peer-reviewed academic journals, presented at scientific meetings, and disseminated to patients' organizations and media outlets. TRIAL REGISTRATION: Trial registration number: NCT04230421. Date March 1, 2021. Version 1.

Smartphone-based fluorescence spectroscopic device for cervical precancer diagnosis: a random forest classification of in vitro data.

Cervical cancer can be treated and cured if diagnosed at an early stage. Optical devices, developed on smartphone-based platforms, are being tested for this purpose as they are cost-effective, robust, and field portable, showing good efficiency compared to the existing commercial devices. This study reports on the applicability of a 3D printed smartphone-based spectroscopic device (3D-SSD) for the early diagnosis of cervical cancer. The proposed device has the ability to evaluate intrinsic fluorescence (IF) from the collected polarized fluorescence (PF) and elastic-scattering (ES) spectra from cervical tissue samples of different grades. IF spectra of 30 cervical tissue samples have been analyzed and classified using a combination of principal component analysis (PCA) and random forest (RF)-based multi-class classification algorithm with an overall accuracy above 90%. The usage of smartphone for image collection, spectral data analysis, and display makes this device a potential contender for use in clinics as a regular screening tool.