Mobile Phone Sensing Systems: A Survey Khan, W. Z.; Yang Xiang; Aalsalem, M. Y. ...
IEEE Communications surveys and tutorials,
01/2013, Volume:
15, Issue:
1
Journal Article
Peer reviewed
Mobile phone sensing is an emerging area of interest for researchers as smart phones are becoming the core communication device in people's everyday lives. Sensor enabled mobile phones or smart ...phones are hovering to be at the center of a next revolution in social networks, green applications, global environmental monitoring, personal and community healthcare, sensor augmented gaming, virtual reality and smart transportation systems. More and more organizations and people are discovering how mobile phones can be used for social impact, including how to use mobile technology for environmental protection, sensing, and to leverage just-in-time information to make our movements and actions more environmentally friendly. In this paper we have described comprehensively all those systems which are using smart phones and mobile phone sensors for humans good will and better human phone interaction.
This communication proposes a wideband decoupling technique to suppress the strong coupling between two extremely closely spaced open-slot antennas and implements a wideband integrated slot antenna ...pair for fifth-generation (5G) metal-rimmed smartphones. By simply inserting a connecting line between two closely spaced open-slot antennas, a top slot structure can be constituted with odd- and even-mode resonances in the lower and higher bands, respectively, to cancel the original strong mutual coupling. In addition to the decoupling effect, the top slot can also expand the effective radiation aperture of the antenna pair for the bandwidth improvement. The proposed slot antenna pair, with a compact footprint of <inline-formula> <tex-math notation="LaTeX">28 \,\, \times 7\,\,\times1.8 </tex-math></inline-formula> mm 3 , shows good impedance matching, isolated and diversity performance across 3.3-5.0 GHz. Then, an <inline-formula> <tex-math notation="LaTeX">8 \times 8 </tex-math></inline-formula> multiple-input multiple-output (MIMO) system, constituted by four sets of slot antenna pairs, is simulated, fabricated, and measured. Both the simulated and experimental results show that the <inline-formula> <tex-math notation="LaTeX">8 \times 8 </tex-math></inline-formula> MIMO system can offer isolations of better than 10.8 dB and envelope correlation coefficients (ECCs) of less than 0.14 between all eight ports across 3.3-5.0 GHz. Also, a total efficiency of 55.0%-83.1% and 52.5%-83.1% is achieved for Ant1 and Ant2, respectively. Featuring wide bandwidth, compact size, high integration level, and metal rim compatibility, we forecast the proposed solution has great potential for future 5G smartphones.
Abstract
Objective
Frontal plane knee alignment plays an integral role in tibiofemoral knee osteoarthritis development and progression. Accessible methods for obtaining direct or indirect measures of ...knee alignment may help inform clinical decision making when specialized equipment is unavailable. The present study evaluated the concurrent validity, as well as intersession (within-rater) and interrater (within-session) reliability of smartphone inclinometry for measuring static frontal plane tibial alignment—a known proxy of frontal plane knee alignment.
Methods
Twenty healthy individuals and 38 patients with knee osteoarthritis were measured for frontal plane tibial alignment by a pair of raters using smartphone inclinometry, manual inclinometry, and 3-dimensional motion capture simultaneously. Healthy participants were measured on 2 separate days. Bland-Altman analysis, supplemented with intraclass correlation coefficient (ICC)(2,k), was used to assess concurrent validity. ICC(2,k), SEM, and minimum detectable change with 95% confidence limits (MDC95) were used to assess measurement reliability.
Results
Compared against motion capture, smartphone inclinometry measured frontal plane tibial alignment with a mean difference of 0.7 and 1.1 degrees (biased toward varus) for healthy participants and participants with knee osteoarthritis, respectively (ICC2,k ≥ 0.87). Smartphone inclinometry measurements demonstrated adequate intersession (within-rater) relative (ICC2,k = 0.91) and absolute (SEM = 0.7 degrees; MDC95 = 1.8 degrees) reliability, which outperformed manual inclinometry (ICC2,k = 0.85; SEM = 1.0 degrees; MDC95 = 2.6 degrees). Interrater (within-session) reliability of smartphone inclinometry was acceptable in both cohorts (ICC2,k = 0.93; SEM = 0.4 degrees to 1.2 degrees; MDC95 = 1.2 degrees to 3.2 degrees).
Conclusion
Smartphone inclinometry is sufficiently valid and reliable for measuring frontal plane tibial alignment in healthy individuals and patients with medial tibiofemoral knee osteoarthritis.
Impact
Smartphones are readily accessible by clinicians and researchers. Our assessment of measurement validity and reliability supports the use of smartphone inclinometry as a clinically available tool to measure frontal plane tibial alignment without medical imaging or specialized equipment.
Background: Despite known association of internet addiction with a reduced brain volume and abnormal connectivity, the impact of excessive smartphone use remains unclear. Methods: PubMed, Embase, ...ClinicalTrial.gov, and Web of Science databases were systematically searched from inception to July 2022 using appropriate keywords for observational studies comparing differences in brain volumes and activations between excessive smartphone users and individuals with regular use by magnetic resonance imaging. Results: Of the 11 eligible studies retrieved from 6993 articles initially screened, seven and six evaluated brain volumes and activations, respectively. The former enrolled 421 participants (165 excessive smartphone users vs. 256 controls), while the latter recruited 276 subjects with 139 excessive smartphone users. The results demonstrated a smaller brain volume in excessive smartphone users compared to the controls (g = −0.55, p < 0.001), especially in subcortical regions (p < 0.001). Besides, the impact was more pronounced in adolescents than in adults (p < 0.001). Regression analysis revealed a significant positive association between impulsivity and volume reduction. Regarding altered activations, the convergences of foci in the declive of the posterior lobe of cerebellum, the lingual gyrus, and the middle frontal gyrus were noted. Conclusions: Our findings demonstrated a potential association of excessive smartphone use with a reduced brain volume and altered activations.
The aim of this study was to assess the prevalence of static balance impairment in university student smartphone users with subclinical neck pain and identify the associated risk factors. Because of ...rapid and widespread smartphones use, and the subsequent effect on neck pain in university students, it is essential to determine the prevalence of balance impairment and associated factors in this population. Simple random sampling was completed among eighty-one participants in this cross-sectional study. A self-reported questionnaire, fitted precisely for smartphone users, was used prior to clinical assessment by the Balance Error Scoring System. Both simple and multiple logistic regressions were used to analyze the prevalence of static balance impairment and associated factors. The prevalence of static balance impairment in university student smartphone users with subclinical neck pain was 74.07% (95% CI: 64.32 to 83.82). The significant risk factors were "daily smartphone use ≥ 4 h'' (AOR: 19.24 (95% CI 4.72 to 78.48)
= 0.000), "≥4 years of smartphone use" (AOR: 5.01 (95% CI 1.12 to 22.38)
= 0.035), and "≥7 neck disability index score'' (AOR: 12.91 (95% CI 2.24 to 74.45)
= 0.004). There was a high prevalence of static balance impairment in university smartphone users with subclinical neck pain. University student smartphone users with subclinical neck pain who met at least one of the risk factors should realize their static balance impairment.
Mobile apps for health exist in large numbers today, but oftentimes, consumers do not continue to use them after a brief period of initial usage, are averse toward using them at all, or are unaware ...that such apps even exist. The purpose of our study was to examine and qualitatively determine the design and content elements of health apps that facilitate or impede usage from the users' perceptive.
In 2014, six focus groups and five individual interviews were conducted in the Midwest region of the U.S. with a mixture of 44 smartphone owners of various social economic status. The participants were asked about their general and health specific mobile app usage. They were then shown specific features of exemplar health apps and prompted to discuss their perceptions. The focus groups and interviews were audio recorded, transcribed verbatim, and coded using the software NVivo.
Inductive thematic analysis was adopted to analyze the data and nine themes were identified: 1) barriers to adoption of health apps, 2) barriers to continued use of health apps, 3) motivators, 4) information and personalized guidance, 5) tracking for awareness and progress, 6) credibility, 7) goal setting, 8) reminders, and 9) sharing personal information. The themes were mapped to theories for interpretation of the results.
This qualitative research with a diverse pool of participants extended previous research on challenges and opportunities of health apps. The findings provide researchers, app designers, and health care providers insights on how to develop and evaluate health apps from the users' perspective.
The aim of the study was to determine the short-term longitudinal pathways between smartphone use, smartphone dependency, depressive symptoms, and loneliness among late adolescents.
A two-wave ...longitudinal survey was used using adolescents between the ages of 17 and 20 years. The interval between wave 1 and wave 2 was between 2.5 and 3 months. Using convenience sampling, the total number of participants who completed both waves of data collection was 346. Validated measures assessed smartphone dependency, smartphone use, depressive symptoms, and loneliness. The longitudinal model was tested using path modeling techniques.
Among the 346 participants (33.6% male, mean standard deviation age at wave 1, 19.11 .75 years, 56.9% response rate), longitudinal path models revealed that wave 1 smartphone dependency predicted loneliness (β = .08, standard error SE = .05, p = .043) and depressive symptoms (β = .11, SE = .05, p = .010) at wave 2, loneliness at wave 1 predicted depressive symptoms at wave 2 (β = .21, SE = .05, p < .001), and smartphone use at wave 1 predicted smartphone dependency at wave 2 (β = .08, SE = .05, p = .011).
Considering the rates of smartphone ownership/use among late adolescents (95%), the association between smartphone use and smartphone dependency, and the deleterious effects of loneliness and depression within this population, health practitioners should communicate with patients and parents about the links between smartphone engagement and psychological well-being.
Aims: In light of the rise in research on technological addictions and smartphone addiction in particular, the aim of this paper was to review the relevant literature on the topic of smartphone ...addiction and determine whether this disorder exists or if it does not adequately satisfy the criteria for addiction. Methods: We reviewed quantitative and qualitative
studies on smartphone addiction and analyzed their methods and conclusions to make a determination on the suitability of the diagnosis “addiction” to excessive and problematic smartphone use. Results: Although the majority of research in the field declares that smartphones are addictive or takes the existence of smartphone addiction as granted, we did not find sufficient support from the addiction perspective to confirm the existence of smartphone
addiction at this time. The behaviors observed in the research could be better labeled as problematic or maladaptive smartphone use and their consequences do not meet the severity levels of those caused by addiction. Discussion and
conclusions: Addiction is a disorder with severe effects on physical and psychological health. A behavior may have a similar presentation as addiction in terms of excessive use, impulse control problems, and negative consequences, but that does not mean that it should be considered an addiction. We propose moving away from the addiction framework when studying technological behaviors and using other terms such as “problematic use” to describe them. We recommend that problematic technology use is to be studied in its sociocultural context with an increased focus on its compensatory functions, motivations, and gratifications.
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