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1.
Sensors (Basel) ; 21(11)2021 Jun 02.
Artigo em Inglês | MEDLINE | ID: mdl-34199559

RESUMO

Traditional pattern recognition approaches have gained a lot of popularity. However, these are largely dependent upon manual feature extraction, which makes the generalized model obscure. The sequences of accelerometer data recorded can be classified by specialized smartphones into well known movements that can be done with human activity recognition. With the high success and wide adaptation of deep learning approaches for the recognition of human activities, these techniques are widely used in wearable devices and smartphones to recognize the human activities. In this paper, convolutional layers are combined with long short-term memory (LSTM), along with the deep learning neural network for human activities recognition (HAR). The proposed model extracts the features in an automated way and categorizes them with some model attributes. In general, LSTM is alternative form of recurrent neural network (RNN) which is famous for temporal sequences' processing. In the proposed architecture, a dataset of UCI-HAR for Samsung Galaxy S2 is used for various human activities. The CNN classifier, which should be taken single, and LSTM models should be taken in series and take the feed data. For each input, the CNN model is applied, and each input image's output is transferred to the LSTM classifier as a time step. The number of filter maps for mapping of the various portions of image is the most important hyperparameter used. Transformation on the basis of observations takes place by using Gaussian standardization. CNN-LSTM, a proposed model, is an efficient and lightweight model that has shown high robustness and better activity detection capability than traditional algorithms by providing the accuracy of 97.89%.


Assuntos
Aprendizado Profundo , Algoritmos , Atividades Humanas , Humanos , Redes Neurais de Computação , Smartphone
2.
Sensors (Basel) ; 21(12)2021 Jun 08.
Artigo em Inglês | MEDLINE | ID: mdl-34201268

RESUMO

The subjectiveness of pain can lead to inaccurate prescribing of pain medication, which can exacerbate drug addiction and overdose. Given that pain is often experienced in patients' homes, there is an urgent need for ambulatory devices that can quantify pain in real-time. We implemented three time- and frequency-domain electrodermal activity (EDA) indices in our smartphone application that collects EDA signals using a wrist-worn device. We then evaluated our computational algorithms using thermal grill data from ten subjects. The thermal grill delivered a level of pain that was calibrated for each subject to be 8 out of 10 on a visual analog scale (VAS). Furthermore, we simulated the real-time processing of the smartphone application using a dataset pre-collected from another group of fifteen subjects who underwent pain stimulation using electrical pulses, which elicited a VAS pain score level 7 out of 10. All EDA features showed significant difference between painless and pain segments, termed for the 5-s segments before and after each pain stimulus. Random forest showed the highest accuracy in detecting pain, 81.5%, with 78.9% sensitivity and 84.2% specificity with leave-one-subject-out cross-validation approach. Our results show the potential of a smartphone application to provide near real-time objective pain detection.


Assuntos
Dor Aguda , Punho , Resposta Galvânica da Pele , Humanos , Smartphone , Articulação do Punho
3.
Talanta ; 233: 122602, 2021 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-34215090

RESUMO

A smartphone-based technique for determining the titration equivalence point from a linear-segment curve was developed for the first time. In this method, a titrant in an increasing microliter-volume was added to a set of sample aliquots containing an indicator covering both sides of the equivalence point. The solutions were subsequently photographed in one shot, in a dark box using a smartphone camera and an illuminating screen of a tablet or light emitting diode lamps arranged below a white acrylic sheet as a light source. After the colors of the solutions were delineated to Red, Green, and Blue (RGB) values, 1/log G was used to construct a plot in which the equivalence point was located at the intersection of the two lines in the region before and after the equivalence point. The technique was successfully applied to the miniaturized titration of sodium chloride injections, showing the good linear relationship of equivalence points to the sodium chloride concentration in the range of 0.4163-0.9675% w/v (R2 of 0.9998). The assay was accurate (% recovery of 98.92-100.52), precise (% relative standard deviation ≤ 1.20), and unaffected by the use of different types of microplates, smartphones, and RGB analysis tools. Additionally, it required no expensive nor complicated equipment and offered the possibility of performing analysis on a single smartphone device when it was used with a mobile application developed to aid data processing and immediate production of reports of analytical results.


Assuntos
Smartphone , Cloreto de Sódio , Colorimetria , Comprimidos
4.
Sensors (Basel) ; 21(12)2021 Jun 13.
Artigo em Inglês | MEDLINE | ID: mdl-34199235

RESUMO

One third of fatal car accidents and so many tragedies are due to alcohol abuse. These sad numbers could be mitigated if everyone had access to a breathalyzer anytime and anywhere. Having a breathalyzer built into a phone or wearable technology could be the way to get around reluctance to carry a separate device. With this goal, we propose an inexpensive breathalyzer that could be integrated in the screens of mobile devices. Our technology is based on the evaporation rate of the fog produced by the breath on the phone screen, which increases with increasing breath alcohol content. The device simply uses a photodiode placed on the side of the screen to measure the signature of the scattered light intensity from the phone display that is guided through the stress layer of the Gorilla glass screen. A part of the display light is coupled to the stress layer via the evanescent field induced at the edge of the breath microdroplets. We demonstrate that the intensity signature measured at the detector can be linked to blood alcohol content. We fabricated a prototype in a smartphone case powered by the phone's battery, controlled by an application installed on the smartphone, and tested it in real-world environments. Limitations and future work toward a fully operational device are discussed.


Assuntos
Smartphone , Dispositivos Eletrônicos Vestíveis , Concentração Alcoólica no Sangue , Testes Respiratórios , Luz
5.
Sensors (Basel) ; 21(13)2021 Jul 01.
Artigo em Inglês | MEDLINE | ID: mdl-34282793

RESUMO

Poor sleep quality or disturbed sleep is associated with multiple health conditions. Sleep position affects the severity and occurrence of these complications, and positional therapy is one of the less invasive treatments to deal with them. Sleep positions can be self-reported, which is unreliable, or determined by using specific devices, such as polysomnography, polygraphy or cameras, that can be expensive and difficult to employ at home. The aim of this study is to determine how smartphones could be used to monitor and treat sleep position at home. We divided our research into three tasks: (1) develop an Android smartphone application ('SleepPos' app) which monitors angle-based high-resolution sleep position and allows to simultaneously apply positional treatment; (2) test the smartphone application at home coupled with a pulse oximeter; and (3) explore the potential of this tool to detect the positional occurrence of desaturation events. The results show how the 'SleepPos' app successfully determined the sleep position and revealed positional patterns of occurrence of desaturation events. The 'SleepPos' app also succeeded in applying positional therapy and preventing the subjects from sleeping in the supine sleep position. This study demonstrates how smartphones are capable of reliably monitoring high-resolution sleep position and provide useful clinical information about the positional occurrence of desaturation events.


Assuntos
Aplicativos Móveis , Smartphone , Estudos Transversais , Humanos , Multimorbidade , Sono , Decúbito Dorsal
6.
Sensors (Basel) ; 21(13)2021 Jul 03.
Artigo em Inglês | MEDLINE | ID: mdl-34283101

RESUMO

We present a smartphone-based indoor localisation system, able to track pedestrians over multiple floors. The system uses Pedestrian Dead Reckoning (PDR), which exploits data from the smartphone's inertial measurement unit to estimate the trajectory. The PDR output is matched to a scaled floor plan and fused with model-based WiFi received signal strength fingerprinting by a Backtracking Particle Filter (BPF). We proposed a new Viterbi-based floor detection algorithm, which fuses data from the smartphone's accelerometer, barometer and WiFi RSS measurements to detect stairs and elevator usage and to estimate the correct floor number. We also proposed a clustering algorithm on top of the BPF to solve multimodality, a known problem with particle filters. The proposed system relies on only a few pre-existing access points, whereas most systems assume or require the presence of a dedicated localisation infrastructure. In most public buildings and offices, access points are often available at smaller densities than used for localisation. Our system was extensively tested in a real office environment with seven 41 m × 27 m floors, each of which had two WiFi access points. Our system was evaluated in real-time and batch mode, since the system was able to correct past states. The clustering algorithm reduced the median position error by 17% in real-time and 13% in batch mode, while the floor detection algorithm achieved a 99.1% and 99.7% floor number accuracy in real-time and batch mode, respectively.


Assuntos
Pedestres , Algoritmos , Elevadores e Escadas Rolantes , Humanos , Smartphone , Caminhada
7.
Artigo em Inglês | MEDLINE | ID: mdl-34205284

RESUMO

Modern technologies surround people every day, including seniors. The aim of this pilot study was to create a maximally user-friendly mobile application in order to meet older users' individual needs. The research sample consisted of 13 older individuals at the age of 55+ years with a mean age of 67 years, living in the Czech Republic. The key assessment tools of this pilot study were the developed application and usability testing. The findings confirmed that the newly developed mobile application for teaching English met the needs of cognitively healthy seniors, and was acceptable and feasible. In addition, it indicated what technical (e.g., visual interface or easy navigation) and pedagogical (e.g., an instructional manual or adjusting to seniors' learning pace or clear instructions) aspects should be strictly followed when designing such an educational smartphone application. In addition, the authors of this pilot study provide several implications for pedagogical practice. Further research should include more empirical studies aimed at the exploration of educational mobile applications for older generation groups with respect to meeting their individual needs in order to enhance their overall well-being. However, such studies are, nowadays, very rare.


Assuntos
Aplicativos Móveis , Smartphone , Idoso , República Tcheca , Nível de Saúde , Humanos , Pessoa de Meia-Idade , Projetos Piloto
8.
Artigo em Inglês | MEDLINE | ID: mdl-34200762

RESUMO

In recent years, there has been a significant increase in global smartphone usage driven by different purposes. This study aimed to explore the effect of smartphone usage on neck muscle (flexors and extensors) endurance, hand grip, and pinch strength among young, healthy college students. In total, 40 male students were recruited for this study; 20 of them belonged to the smartphone-addicted group, while the other 20 were in the non-addicted group based on their smartphone addiction scale-short version (SAS-SV) scores (the threshold for determining smartphone addiction: 31/60). Neck flexor endurance time, the ability to perform a neck extensor muscle endurance test, and hand and pinch grip strength were assessed. Multivariate analysis of variance (MANOVA) was used to assess between-group differences in the mean values of neck flexor endurance time, hand grip, and pinch grip. A significant group effect (Wilks' lambda = 0.51, F (5,34) = 6.34, p = 0.001, partial eta squared = 0.48) was found. A decrease in neck flexor endurance time was observed in the smartphone-addicted group compared with that of the non-addicted group (p < 0.001). However, there was no notable difference in the neck extensor muscle endurance test or in hand grip and pinch grip strength of both hands between groups (p > 0.05). Using a smartphone for a prolonged time might affect neck flexor muscle endurance; however, more research is needed to explore the long-term effects of using smartphones on neck muscle endurance and hand/pinch grip strength and the risk of developing upper limb neuromusculoskeletal dysfunction.


Assuntos
Força de Pinça , Smartphone , Estudos Transversais , Mãos , Força da Mão , Humanos , Masculino , Músculos do Pescoço , Estudantes
9.
Bone Joint J ; 103-B(7 Supple B): 91-97, 2021 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-34192907

RESUMO

AIMS: The purpose of this study is to evaluate early outcomes with the use of a smartphone-based exercise and educational care management system after total hip arthroplasty (THA) and demonstrate decreased use of in-person physiotherapy (PT). METHODS: A multicentre, prospective randomized controlled trial was conducted to evaluate a smartphone-based care platform for primary THA. Patients randomized to the control group (198) received the institution's standard of care. Those randomized to the treatment group (167) were provided with a smartwatch and smartphone application. PT use, THA complications, readmissions, emergency department/urgent care visits, and physician office visits were evaluated. Outcome scores include the Hip disability and Osteoarthritis Outcome Score (HOOS, JR), health-related quality-of-life EuroQol five-dimension five-level score (EQ-5D-5L), single leg stance (SLS) test, and the Timed Up and Go (TUG) test. RESULTS: The control group was significantly younger by a mean 3.0 years (SD 9.8 for control, 10.4 for treatment group; p = 0.007), but there were no significant differences between groups in BMI, sex, or preoperative diagnosis. Postoperative PT use was significantly lower in the treatment group (34%) than in the control group (55.4%; p = 0.001). There were no statistically significant differences in complications, readmissions, or outpatient visits. The 90-day outcomes showed no significant differences in mean hip flexion between controls (101° (SD 10.8)) and treatment (100° (SD 11.3); p = 0.507) groups. The HOOS, JR scores were not significantly different between control group (73 points (SD 13.8)) and treatment group (73.6 points (SD 13); p = 0.660). Mean 30-day SLS time was 22.9 seconds (SD 19.8) in the control group and 20.7 seconds (SD 19.5) in the treatment group (p = 0.342). Mean TUG time was 11.8 seconds (SD 5.1) for the control group and 11.9 (SD 5) seconds for the treatment group (p = 0.859). CONCLUSION: The use of the smartphone care management system demonstrated similar early outcomes to those achieved using traditional care models, along with a significant decrease in PT use. Noninferiority was demonstrated with regard to complications, readmissions, and ED and urgent care visits. This technology allows patients to rehabilitate on a more flexible schedule and avoid unnecessary healthcare visits, as well as potentially reducing overall healthcare costs. Cite this article: Bone Joint J 2021;103-B(7 Supple B):91-97.


Assuntos
Artroplastia de Quadril/reabilitação , Educação de Pacientes como Assunto , Período Pós-Operatório , Autocuidado , Smartphone , Avaliação da Deficiência , Serviço Hospitalar de Emergência/estatística & dados numéricos , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Visita a Consultório Médico/estatística & dados numéricos , Readmissão do Paciente/estatística & dados numéricos , Modalidades de Fisioterapia , Complicações Pós-Operatórias/epidemiologia , Estudos Prospectivos , Qualidade de Vida
10.
Artigo em Inglês | MEDLINE | ID: mdl-34204871

RESUMO

BACKGROUND: mobile applications (apps) facilitate cancer pain ecological momentary assessment (EMA) and provide more reliable data than retrospective monitoring. The aims of this study are (a) to describe the status of persons with cancer pain when assessed ecologically, (b) to analyze the utility of clinical alarms integrated into the app, and (c) to test the feasibility of implementing an app for daily oncological pain monitoring. METHODS: in this feasibility study, 21 patients (mean age = 56.95 years, SD = 10.53, 81.0% men) responded to an app-based evaluation of physical status (baseline and breakthrough cancer pain (BTcP)) and mental health variables (fatigue, mood, and coping) daily during 30 days. RESULTS: cancer pain characterization with the app was similar to data from the literature using retrospective assessments in terms of BTcP duration and perceived medication effectiveness. However, BTcP was less frequent when evaluated ecologically. Pain, fatigue, and mood were comparable in the morning and evening. Passive coping strategies were the most employed daily. Clinical alarms appear to be useful to detect and address adverse events. App implementation was feasible and acceptable. CONCLUSION: apps reduce recall bias and facilitate a rapid response to adverse events in oncological care. Future efforts should be addressed to integrate EMA and ecological momentary interventions to facilitate pain self-management via apps.


Assuntos
Dor do Câncer , Aplicativos Móveis , Neoplasias , Dor do Câncer/diagnóstico , Dor do Câncer/terapia , Avaliação Momentânea Ecológica , Estudos de Viabilidade , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Neoplasias/complicações , Estudos Retrospectivos , Smartphone
11.
Artigo em Inglês | MEDLINE | ID: mdl-34205947

RESUMO

BACKGROUND: Smartphones are an important part of children's and adolescents' lives, and they often spend a lot of time using them. This study aims to precisely discover the effects of smartphone addiction on sleep duration as moderated by age and gender. MATERIALS AND METHODS: The data utilized in this study are from the 'Korean Children and Youth Panel Survey 2018' by the National Youth Policy Institute; a total of 4940 youths (2399 in grade 4 and 2541 in grade 7) from the survey were analyzed by Stata 15.0 S. The dependent variable is sleep duration, and the independent variables are the sub-factors of smartphone addiction: disturbance of adaptive functions, virtual life orientation, withdrawal, and tolerance. An independent t-test was conducted to confirm the differences in the main variables according to gender and age. Multiple regression analysis was conducted to verify the moderating effects of gender and age in the relationship between children's smartphone addiction and sleep duration. RESULTS: First, the average sleep duration among grade 4 students was 9.17 h and grade 7 students was 7.96 h. Second, sleep duration was significantly higher for males than females, while there was no difference in smartphone addiction by gender. Third, smartphone addiction, particularly the sub-factor of tolerance significantly affected sleep duration. Fourth, age significantly affected sleep duration and gender had a moderating effect on sleep duration. CONCLUSIONS: Interventions to develop a healthy smartphone usage culture on family and societal levels would be beneficial for increasing awareness of smartphone addiction and its adverse effects on children and adolescents. Furthermore, targeted intervention would be more effective at modifying addictive behavior and sleep duration than trying to administer blanket interventions to youths as a whole.


Assuntos
Comportamento Aditivo , Transtorno de Adição à Internet , Adolescente , Comportamento Aditivo/epidemiologia , Criança , Feminino , Humanos , Masculino , Sono , Smartphone , Inquéritos e Questionários
12.
Spectrochim Acta A Mol Biomol Spectrosc ; 262: 120135, 2021 Dec 05.
Artigo em Inglês | MEDLINE | ID: mdl-34243139

RESUMO

Malononitrile can be transformed into hypertoxic hydrogen cyanide which induces severely jeopardizes to human beings and environment. However, an effective detection technology for malononitrile was still lacking, which means that it is necessary to develop new sensitive analysis technology for malononitrile. Here in, a high sensitive fluorescent probe NQBS for detecting malononitrile was designed and synthesized from the derivative of natural product nopinone. NQBS could selectively recognize malononitrile from 26 kinds of competitive compounds in N, N-dimethylformamide (DMF) solution. The detection limit of NQBS for malononitrile was calculated to be 1.96 µM at the concentration range of 0-25 µM. In addition, the sensing mechanism of NQBS towards malononitrile was proved with high resolution mass spectrometer (HRMS), nuclear magnetic resonance hydrogen spectroscopy (1H NMR), and density functional theory (DFT) calculation analysis as Knoevenagel condensation process and intramolecular cyclization reaction. With the assistance of smartphone and color recognition software, NQBS was well applied in the on-site recognition of malononitrile in real time by analyzing the change trend of the red-greenblue (RGB) value of the NQBS solution.


Assuntos
Nitrilas , Smartphone , Corantes Fluorescentes , Humanos
13.
Artigo em Inglês | MEDLINE | ID: mdl-34203674

RESUMO

While smartphone addiction is becoming a recent concern with the exponential increase in the number of smartphone users, it is difficult to predict problematic smartphone users based on the usage characteristics of individual smartphone users. This study aimed to explore the possibility of predicting smartphone addiction level with mobile phone log data. By Korea Internet and Security Agency (KISA), 29,712 respondents completed the Smartphone Addiction Scale developed in 2017. Integrating basic personal characteristics and smartphone usage information, the data were analyzed using machine learning techniques (decision tree, random forest, and Xgboost) in addition to hypothesis tests. In total, 27 variables were employed to predict smartphone addiction and the accuracy rate was the highest for the random forest (82.59%) model and the lowest for the decision tree model (74.56%). The results showed that users' general information, such as age group, job classification, and sex did not contribute much to predicting their smartphone addiction level. The study can provide directions for future work on the detection of smartphone addiction with log-data, which suggests that more detailed smartphone's log-data will enable more accurate results.


Assuntos
Telefone Celular , Smartphone , Transtorno de Adição à Internet , Aprendizado de Máquina , República da Coreia
14.
BMC Infect Dis ; 21(1): 681, 2021 Jul 13.
Artigo em Inglês | MEDLINE | ID: mdl-34256724

RESUMO

BACKGROUND: Mobile phones used by healthcare workers (HCWs) are contaminated with bacteria, but the posterior surface of smartphones has rarely been studied. The aim of this study was to compare the prevalence of microbial contamination of touchscreens and posterior surfaces of smartphones owned by HCWs. METHODS: A cross-sectional study of smartphones used by HCWs employed at two intensive care units at a Japanese tertiary care hospital was performed. Bacteria on each surface of the smartphones were isolated separately. The primary outcomes were the prevalence of microbial contamination on each surface of smartphones and associated bacterial species. Fisher's exact test was used to compare dichotomous outcomes. RESULTS: Eighty-four HCWs participated in this study. The touchscreen and posterior surface were contaminated in 27 (32.1%) and 39 (46.4%) smartphones, respectively, indicating that the posterior surface was more frequently contaminated (p = 0.041). Bacillus species and coagulase-negative staphylococci were isolated from each surface of the smartphones. CONCLUSIONS: The posterior surface of a smartphone was more significantly contaminated with bacteria than the touchscreen, regardless of having a cover. Therefore, routine cleaning of the posterior surface of a smartphone is recommended.


Assuntos
Bacillus/isolamento & purificação , Contaminação de Equipamentos , Pessoal de Saúde/estatística & dados numéricos , Smartphone , Staphylococcus/isolamento & purificação , Infecção Hospitalar/prevenção & controle , Estudos Transversais , Contaminação de Equipamentos/prevenção & controle , Contaminação de Equipamentos/estatística & dados numéricos , Humanos , Controle de Infecções/métodos , Unidades de Terapia Intensiva/estatística & dados numéricos , Japão , Prevalência
15.
Sci Rep ; 11(1): 14421, 2021 07 13.
Artigo em Inglês | MEDLINE | ID: mdl-34257350

RESUMO

A plethora of measures are being combined in the attempt to reduce SARS-CoV-2 spread. Due to its sustainability, contact tracing is one of the most frequently applied interventions worldwide, albeit with mixed results. We evaluate the performance of digital contact tracing for different infection detection rates and response time delays. We also introduce and analyze a novel strategy we call contact prevention, which emits high exposure warnings to smartphone users according to Bluetooth-based contact counting. We model the effect of both strategies on transmission dynamics in SERIA, an agent-based simulation platform that implements population-dependent statistical distributions. Results show that contact prevention remains effective in scenarios with high diagnostic/response time delays and low infection detection rates, which greatly impair the effect of traditional contact tracing strategies. Contact prevention could play a significant role in pandemic mitigation, especially in developing countries where diagnostic and tracing capabilities are inadequate. Contact prevention could thus sustainably reduce the propagation of respiratory viruses while relying on available technology, respecting data privacy, and most importantly, promoting community-based awareness and social responsibility. Depending on infection detection and app adoption rates, applying a combination of digital contact tracing and contact prevention could reduce pandemic-related mortality by 20-56%.


Assuntos
COVID-19/prevenção & controle , Busca de Comunicante/métodos , Smartphone , Humanos , Pandemias/prevenção & controle , SARS-CoV-2/patogenicidade
16.
Biosensors (Basel) ; 11(6)2021 Jun 05.
Artigo em Inglês | MEDLINE | ID: mdl-34198935

RESUMO

There is currently no objective portable screening modality for narrow angles in the community. In this prospective, single-centre image validation study, we used machine learning on slit lamp images taken with a portable smartphone device (MIDAS) to predict the central anterior chamber depth (ACD) of phakic patients with undilated pupils. Patients 60 years or older with no history of laser or intraocular surgery were recruited. Slit lamp images were taken with MIDAS, followed by anterior segment optical coherence tomography (ASOCT; Casia SS-1000, Tomey, Nagoya, Japan). After manual annotation of the anatomical landmarks of the slit lamp photos, machine learning was applied after image processing and feature extraction to predict the ACD. These values were then compared with those acquired from the ASOCT. Sixty-six eyes (right = 39, 59.1%) were included for analysis. The predicted ACD values formed a strong positive correlation with the measured ACD values from ASOCT (R2 = 0.91 for training data and R2 = 0.73 for test data). This study suggests the possibility of estimating central ACD using slit lamp images taken from portable devices.


Assuntos
Câmara Anterior , Aprendizado de Máquina , Lâmpada de Fenda , Smartphone , Idoso , Câmara Anterior/anatomia & histologia , Humanos , Pessoa de Meia-Idade
17.
Front Public Health ; 9: 568822, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34222160

RESUMO

Smartphone technologies can support older adults in their daily lives as they age in place at home. However, they may struggle to use these technologies which impacts acceptance, adoption, and sustainable use. Peer to peer community learning has the potential to support older adults to learn using (smartphone) technologies. This paper studies such a learning community approach and how it can support older adults to learn using and adopt the smartphone application GoLivePhone. This technology assists older adults in their daily living by supporting them through fall detection and activity tracking. In particular, the interface of this application can evolve and adapt as older adults become more knowledgeable during the use process or as their abilities change. This paper shows a field study with seven older adults learning and using the GoLivePhone technology through a living lab approach. These older adults participated in this research in a technology learning community that was set-up for research purposes. For this we used ordinary Samsung A3 smartphones with the simplified GoLivePhone software, particularly designed for older adults. At the end of the learning class we conducted an additional focus group to both explore factors facilitating older adults to learn using this technology and to identify their main personal drivers and motivators to start and adopt this technology. We collected qualitative data via open questions and audio recording during the focus group. This collected data was subject to a thematic analysis, coding was primarily performed by the first author, and reviewed by the other authors. We provide insights into how peer to peer community learning can contribute, and found both super-users and recall tools to be helpful to support sustainable use of smartphone technology to support older adults to age in place.


Assuntos
Smartphone , Aprendizado Social , Grupos Focais , Aprendizagem , Tecnologia
18.
Medicine (Baltimore) ; 100(27): e26526, 2021 Jul 09.
Artigo em Inglês | MEDLINE | ID: mdl-34232186

RESUMO

ABSTRACT: Smartphone alerting systems (SAS) for first responders potentially shorten the resuscitation-free interval of patients with acute cardiac arrest. During the corona virus disease-19 (COVID-19) pandemic, many systems are suspended due to potential risks for the responders.Objective of the study was to establish a concept for SAS during the COVID-19 pandemic and to evaluate whether a SAS can safely be operated in pandemic conditions.A SAS had been implemented in Freiburg (Germany) in 2018 alerting nearby registered first responders in case of emergencies with suspected cardiac arrest. Due to the pandemic, SAS was stopped in March 2020. A concept for a safe restart was elaborated with provision of a set with ventilation bag/mask, airway filter, and personal protective equipment (PPE) for every volunteer. A standard operating procedure was elaborated following the COVID-19 guidelines of the European Resuscitation Council.Willingness of the participants to respond alarms during the pandemic was investigated using an online survey. The response rates of first responders were monitored before and after deactivation, and during the second wave of the pandemic.The system was restarted in May 2020. The willingness to respond to alarms was lower during the pandemic without PPE. It remained lower than before the pandemic when the volunteers had been equipped with PPE, but the alarm response rate remained at approximately 50% during the second wave of the pandemic.When volunteers are equipped with PPE, the operation of a SAS does not need to be paused, and the willingness to respond remains high among first responders.


Assuntos
COVID-19/epidemiologia , Transmissão de Doença Infecciosa do Paciente para o Profissional/prevenção & controle , Pandemias , Equipamento de Proteção Individual , Smartphone , Socorristas , Alemanha/epidemiologia , Humanos , Estudos Retrospectivos , SARS-CoV-2
19.
Sensors (Basel) ; 21(14)2021 Jul 07.
Artigo em Inglês | MEDLINE | ID: mdl-34300402

RESUMO

In this work, we propose a Bluetooth low energy (BLE) beacon-based algorithm to enable remote measurement of the social behavior of the participants of an observational Autism Spectrum Disorder (ASD) clinical trial (NCT03611075). We have developed a mobile application for a smartphone and a smartwatch to collect beacon signals from BLE beacon sensors as well as to store information about the participants' household rooms. Our goal is to collect beacon information about the time the participants spent in different rooms of their household to infer sociability information. We applied the same technology and setup in an internal experiment with healthy volunteers to evaluate the accuracy of the proposed algorithm in 10 different home setups, and we observed an average accuracy of 97.2%. Moreover, we show that it is feasible for the clinical study participants/caregivers to set up the BLE beacon sensors in their homes without any technical help, with 96% of them setting up the technology on the first day of data collection. Next, we present results from one-week location data from study participants collected through the proposed technology. Finally, we provide a list of good practice guidelines for optimally applying beacon technology for indoor location monitoring. The proposed algorithm enables us to estimate time spent in different rooms of a household that can pave the development of objective sociability features and eventually support decisions regarding drug efficacy in ASD.


Assuntos
Transtorno do Espectro Autista , Aplicativos Móveis , Transtorno do Espectro Autista/diagnóstico , Estudos de Viabilidade , Humanos , Smartphone , Comportamento Social
20.
Sensors (Basel) ; 21(14)2021 Jul 09.
Artigo em Inglês | MEDLINE | ID: mdl-34300445

RESUMO

Constant light power operation of an ultraviolet (UV) LED based on portable low-cost instrumentation and a monolithically integrated monitoring photodiode (MPD) has been reported for the first time. UV light irradiation has become one of the essential measures for disinfection and sterilization. Monitoring and maintaining a specified light power level is important to meet the criteria of sterilization. We built a module composed of a monolithically integrated UV LED and MPD, a transimpedance amplifier, an Arduino Uno card, a digital-to-analog converter and a Bluetooth transceiver. An Android App that we wrote remotely controlled the UV LED module via Bluetooth. The Arduino Uno card was programmed to receive demands from the smartphone, sent a driving voltage to the LED and returned the present MPD voltage to the smartphone. A feedback loop was used to adjust the LED voltage for maintaining a constant light output. We successfully demonstrated the functioning of remote control of the App, and the resultant UV LED measured power remained the same as the setting power. This setup can also be applied to visible or white LEDs for controlling/maintaining mixed light's chromaticity coordinates or color temperature. With such controlling and internet capability, custom profiling and maintenance of precision lighting remotely would be possible.


Assuntos
Desinfecção , Smartphone , Iluminação , Raios Ultravioleta
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