mSpray: a mobile phone technology to improve malaria control efforts and monitor human exposure to malaria control pesticides in Limpopo, South Africa

Recent estimates indicate that malaria has led to over half a million deaths worldwide, mostly to African children. Indoor residual spraying (IRS) of insecticides is one of the primary vector control interventions. However, current reporting systems do not obtain precise location of IRS events in relation to malaria cases, which poses challenges for effective and efficient malaria control. This information is also critical to avoid unnecessary human exposure to IRS insecticides. We developed and piloted a mobile-based application (mSpray) to collect comprehensive information on IRS spray events. We assessed the utility, acceptability and feasibility of using mSpray to gather improved homestead- and chemical-level IRS coverage data. We installed mSpray on 10 cell phones with data bundles, and pilot tested it with 13 users in Limpopo, South Africa. Users completed basic information (number of rooms/shelters sprayed; chemical used, etc.) on spray events. Upon submission, this information as well as geographic positioning system coordinates and time/date stamp were uploaded to a Google Drive Spreadsheet to be viewed in real time. We administered questionnaires, conducted focus groups, and interviewed key informants to evaluate the utility of the app. The low-cost, cell phone-based "mSpray" app was learned quickly by users, well accepted and preferred to the current paper-based method. We recorded 2865 entries (99.1% had a GPS accuracy of 20 m or less) and identified areas of improvement including increased battery life. We also identified a number of logistic and user problems (e.g., cost of cell phones and cellular bundles, battery life, obtaining accurate GPS measures, user errors, etc.) that would need to be overcome before full deployment. Use of cell phone technology could increase the efficiency of IRS malaria control efforts by mapping spray events in relation to malaria cases, resulting in more judicious use of chemicals that are potentially harmful to humans and the environment.

Short- and long-term effects of real-time medication monitoring with short message service (SMS) reminders for missed doses on the refill adherence of people with Type 2 diabetes: evidence from a randomized controlled trial

AIMS

To investigate short- and long-term effects of real-time monitoring medication use combined with short message service (SMS) reminders for missed doses on refill adherence to oral anti-diabetic medication.

METHODS

A randomized controlled trial with two intervention groups and one control group involving 161 participants with Type 2 diabetes with suboptimal adherence. For 6 months, participants in the SMS group (n = 56) were monitored and received SMS reminders if they missed their medication. Participants in the non-SMS group (n = 48) were only monitored. The control group (n = 57) was not exposed to any intervention. Primary outcome measure was refill adherence to oral anti-diabetic medication. Multi-level regression analyses were performed to examine intervention effects on adherence between and within groups after 1 and 2 years of follow-up.

RESULTS

At baseline, mean refill adherence was comparable between the groups. After 1 year, adherence in the SMS group was significantly higher than in the control group (79.5% vs. 64.5%; P < 0.001) and showed a significant improvement from baseline (+16.3%; P < 0.001). Mean adherence in the non-SMS group reached 73.1% (+7.3%; P < 0.05), but did not differ from the control group (P = 0.06). After 2 years, the improved adherence in the SMS group persisted and remained significantly higher than in the control group (80.4% vs. 68.4%; P < .01), contrary to the non-SMS group whose adherence approached baseline level again (65.5%).

CONCLUSIONS

This study shows the long-term effectiveness of real-time medication monitoring combined with SMS reminders in improving refill adherence. This new reminder system can strengthen the self-management of people with diabetes.

Radio-frequency electromagnetic field (RF-EMF) exposure levels in different European outdoor urban environments in comparison with regulatory limits

BACKGROUND

Concerns of the general public about potential adverse health effects caused by radio-frequency electromagnetic fields (RF-EMFs) led authorities to introduce precautionary exposure limits, which vary considerably between regions. It may be speculated that precautionary limits affect the base station network in a manner that mean population exposure unintentionally increases.

AIMS

The objectives of this multicentre study were to compare mean exposure levels in outdoor areas across four different European cities and to compare with regulatory RF-EMF exposure levels in the corresponding areas.

METHODS

We performed measurements in the cities of Amsterdam (the Netherlands, regulatory limits for mobile phone base station frequency bands: 41-61 V/m), Basel (Switzerland, 4-6 V/m), Ghent (Belgium, 3-4.5 V/m) and Brussels (Belgium, 2.9-4.3 V/m) using a portable measurement device. Measurements were conducted in three different types of outdoor areas (central and non-central residential areas and downtown), between 2011 and 2012 at 12 different days. On each day, measurements were taken every 4s for approximately 15 to 30 min per area. Measurements per urban environment were repeated 12 times during 1 year.

RESULTS

Arithmetic mean values for mobile phone base station exposure ranged between 0.22 V/m (Basel) and 0.41 V/m (Amsterdam) in all outdoor areas combined. The 95th percentile for total RF-EMF exposure varied between 0.46 V/m (Basel) and 0.82 V/m (Amsterdam) and the 99th percentile between 0.81 V/m (Basel) and 1.20 V/m (Brussels).

CONCLUSIONS

All exposure levels were far below international reference levels proposed by ICNIRP (International Commission on Non-Ionizing Radiation Protection). Our study did not find indications that lowering the regulatory limit results in higher mobile phone base station exposure levels.

Association between mobile phone use and semen quality: a systemic review and meta-analysis

Possible hazardous health effects of radiofrequency electromagnetic radiations emitted from mobile phone on the reproductive system have raised public concern in recent years. This systemic review and meta-analysis was prepared following standard procedures of the Cochrane Collaboration and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement and checklist. Relevant studies published up to May 2013 were identified from five major international and Chinese literature databases: Medline/PubMed, EMBASE, CNKI, the VIP database and the Cochrane Central Register of Controlled Trials in the Cochrane Library. Eighteen studies with 3947 men and 186 rats were included in the systemic review, of which 12 studies (four human studies, four in vitro studies and four animal studies) with 1533 men and 97 rats were used in the meta-analyses. Systemic review showed that results of most of the human studies and in vitro laboratory studies indicated mobile phone use or radiofrequency exposure had negative effects on the various semen parameters studied. However, meta-analysis indicated that mobile phone use had no adverse effects on semen parameters in human studies. In the in vitro studies, meta-analysis indicated that radiofrequency radiation had detrimental effect on sperm motility and viability in vitro [pooled mean difference (MDs) (95% CI): -4.11 (-8.08, -0.13), -3.82 (-7.00, -0.65) for sperm motility and viability respectively]. As for animal studies, radiofrequency exposure had harmful effects on sperm concentration and motility [pooled MDs (95% CI): -8.75 (-17.37, -0.12), -17.72 (-32.79, -2.65) for sperm concentration and motility respectively]. Evidence from current studies suggests potential harmful effects of mobile phone use on semen parameters. A further multicentred and standardized study is needed to assess the risk of mobile phone use on the reproductive system.

Metal toxicity assessment of mobile phone parts using Milli Q water

Environmentally safe disposal of end-of-life (EoL) or discarded mobile phone is a serious problem on account of their ever increasing number and toxic metals contents. In the present work, metal toxicity of mobile phone plastics, printed wire boards (PWBs) and batteries were assessed through dynamic batch leaching using Milli Q (MQ) water. Phone plastics failed Toxicity Characterization Leaching Procedure (TCLP) and Waste Extraction Test (WET) for Pb as the cumulative amount of Pb leached from plastics (5.33 mg/l) exceeded the regulatory limits (5.0mg/l) used in characterizing a waste as hazardous. Similarly, the average cumulative amount (21.83 mg/l) of Ni leached from PWBs exceeded the regulatory limit of 20mg/l and thus PWBs failed WET. Metals leached from batteries in small amounts (Cr: 0.40 mg/l and Ni: 0.15 mg/l). The presence of Fe in the batteries and its precipitation as oxides/hydroxides in the leaching solution hindered the leaching of other metals in MQ water. Both plastics and PWBs should be treated as hazardous waste and should not be disposed in open landfills. Further, MQ water leaching could provide good simulation of metals leaching from the mobile phones disposed at landfill sites.

Optimization of remotely delivered intensive lifestyle treatment for obesity using the Multiphase Optimization Strategy: Opt-IN study protocol

BACKGROUND

Obesity-attributable medical expenditures remain high, and interventions that are both effective and cost-effective have not been adequately developed. The Opt-IN study is a theory-guided trial using the Multiphase Optimization Strategy (MOST) to develop an optimized, scalable version of a technology-supported weight loss intervention.

OBJECTIVE

Opt-IN aims to identify which of 5 treatment components or component levels contribute most meaningfully and cost-efficiently to the improvement of weight loss over a 6 month period.

STUDY DESIGN

Five hundred and sixty obese adults (BMI 30-40 kg/m(2)) between 18 and 60 years old will be randomized to one of 16 conditions in a fractional factorial design involving five intervention components: treatment intensity (12 vs. 24 coaching calls), reports sent to primary care physician (No vs. Yes), text messaging (No vs. Yes), meal replacement recommendations (No vs. Yes), and training of a participant's self-selected support buddy (No vs. Yes). During the 6-month intervention, participants will monitor weight, diet, and physical activity on the Opt-IN smartphone application downloaded to their personal phone. Weight will be assessed at baseline, 3, and 6 months.

SIGNIFICANCE

The Opt-IN trial is the first study to use the MOST framework to develop a weight loss treatment that will be optimized to yield the best weight loss outcome attainable for $500 or less.

Effectiveness of a smartphone application to promote physical activity in primary care: the SMART MOVE randomised controlled trial

BACKGROUND

Physical inactivity is a major, potentially modifiable, risk factor for cardiovascular disease, cancer, and other chronic diseases. Effective, simple, and generalisable interventions that will increase physical activity in populations are needed.

AIM

To evaluate the effectiveness of a smartphone application (app) to increase physical activity in primary care.

DESIGN AND SETTING

An 8-week, open-label, randomised controlled trial in rural, primary care in the west of Ireland.

METHOD

Android smartphone users >16 years of age were recruited. All participants were provided with similar physical activity goals and information on the benefits of exercise. The intervention group was provided with a smartphone app and detailed instructions on how to use it to achieve these goals. The primary outcome was change in physical activity, as measured by a daily step count between baseline and follow-up.

RESULTS

A total of 139 patients were referred by their primary care health professional or self-referred. In total, 37 (27%) were screened out and 12 (9%) declined to participate, leaving 90 (65%) patients who were randomised. Of these, 78 provided baseline data (intervention = 37; control = 41) and 77 provided outcome data (intervention = 37; control = 40). The mean daily step count at baseline for intervention and control groups was 4365 and 5138 steps per day respectively. After adjusting, there was evidence of a significant treatment effect (P = 0.009); the difference in mean improvement in daily step count from week 1 to week 8 inclusive was 1029 (95% confidence interval 214 to 1843) steps per day, favouring the intervention. Improvements in physical activity in the intervention group were sustained until the end of the trial.

CONCLUSION

A simple smartphone app significantly increased physical activity over 8 weeks in a primary care population.

A new paradigm for primary prevention strategy in people with elevated risk of stroke

Existing methods of primary stroke prevention are not sufficiently effective. Based on the recently developed Stroke Riskometer app, a new 'mass-elevated risk stroke/cardiovascular disease prevention' approach as an addition to the currently adopted absolute risk stroke/cardiovascular disease prevention approach is being advocated. We believe this approach is far more appealing to the individuals concerned and could be as efficient as the conventional population-based approach because it allows identification and engagement in prevention of all individuals who are at an increased (even slightly increased) risk of stroke and cardiovascular disease. The key novelty of this approach is twofold. First, it utilizes modern far-reaching mobile technologies, allowing individuals to calculate their absolute risk of stroke within the next 5 to 10 years and to compare their risk with those of the same age and gender without risk factors. Second, it employs self-management strategies to engage the person concerned in stroke/cardiovascular disease prevention, which is tailored to the person's individual risk profile. Preventative strategies similar to the Stroke Riskometer could be developed for other non-communicable disorders for which reliable predictive models and preventative recommendations exist. This would help reduce the burden of non-communicable disorders worldwide.

A feasibility study of mobile phone text messaging to support education and management of type 2 diabetes in Iraq

BACKGROUND

We undertook a feasibility study to evaluate feasibility and utility of short message services (SMSs) to support Iraqi adults with newly diagnosed type 2 diabetes.

SUBJECTS AND METHODS

Fifty patients from a teaching hospital clinic in Basrah in the first year after diagnosis were recruited to receive weekly SMSs relating to diabetes self-management over 29 weeks. Numbers of messages received, acceptability, cost, effect on glycated hemoglobin (HbA1c), and diabetes knowledge were documented.

RESULTS

Forty-two patients completed the study, receiving an average 22 of 28 messages. Mean knowledge score rose from 8.6 (SD 1.5) at baseline to 9.9 (SD 1.4) 6 months after receipt of SMSs (P=0.002). Baseline and 6-month knowledge scores correlated (r=0.297, P=0.049). Mean baseline HbA1c was 79 mmol/mol (SD 14 mmol/mol) (9.3% [SD 1.3%]) and decreased to 70 mmol/mol (SD 13 mmol/mol) (8.6% [SD 1.2%]) (P=0.001) 6 months after the SMS intervention. Baseline and 6-month values were correlated (r=0.898, P=0.001). Age, gender, and educational level showed no association with changes in HbA1c or knowledge score. Changes in knowledge score were correlated with postintervention HbA1c (r=-0.341, P=0.027). All patients were satisfied with text messages and wished the service to be continued after the study. The cost of SMSs was €0.065 per message.

CONCLUSIONS

This study demonstrates SMSs are acceptable, cost-effective, and feasible in supporting diabetes care in the challenging, resource-poor environment of modern-day Iraq. This study is the first in Iraq to demonstrate similar benefits of this technology on diabetes education and management to those seen from its use in better-resourced parts of the world. A randomized controlled trial is needed to assess precise benefits on self-care and knowledge.

Somnography using unobtrusive motion sensors and Android-based mobile phones

Sleep plays a fundamental role in the life of every human. The prevalence of sleep disorders has increased significantly, now affecting up to 50% of the general population. Sleep is usually analyzed by extracting a hypnogram containing sleep stages. The gold standard method polysomnography (PSG) requires subjects to stay overnight in a sleep laboratory and to wear a series of obtrusive devices. This work presents an easy to use method to perform somnography at home using unobtrusive motion sensors. Ten healthy male subjects were recorded during two consecutive nights. Sensors from the Shimmer platform were placed in the bed to record accelerometer data, while reference hypnograms were collected using a SOMNOwatch system. A series of filters were used to extract a motion feature in 30 second epochs from the accelerometer signals. The feature was used together with the ground truth information to train a Naive Bayes classifiers that distinguished wakefulness, REM and non-REM sleep. Additionally the algorithm was implemented on an Android mobile phone. Averaged over all subjects, the classifier had a mean accuracy of 79.0 % (SD 9.2%) for the three classes. The mobile phone implementation was able to run in realtime during all experiments. In future this will lead to a method for simple and unobtrusive somnography using mobile phones.

Exploring universal patterns in human home-work commuting from mobile phone data

Home-work commuting has always attracted significant research attention because of its impact on human mobility. One of the key assumptions in this domain of study is the universal uniformity of commute times. However, a true comparison of commute patterns has often been hindered by the intrinsic differences in data collection methods, which make observation from different countries potentially biased and unreliable. In the present work, we approach this problem through the use of mobile phone call detail records (CDRs), which offers a consistent method for investigating mobility patterns in wholly different parts of the world. We apply our analysis to a broad range of datasets, at both the country (Portugal, Ivory Coast, and Saudi Arabia), and city (Boston) scale. Additionally, we compare these results with those obtained from vehicle GPS traces in Milan. While different regions have some unique commute time characteristics, we show that the home-work time distributions and average values within a single region are indeed largely independent of commute distance or country (Portugal, Ivory Coast, and Boston)-despite substantial spatial and infrastructural differences. Furthermore, our comparative analysis demonstrates that such distance-independence holds true only if we consider multimodal commute behaviors-as consistent with previous studies. In car-only (Milan GPS traces) and car-heavy (Saudi Arabia) commute datasets, we see that commute time is indeed influenced by commute distance. Finally, we put forth a testable hypothesis and suggest ways for future work to make more accurate and generalizable statements about human commute behaviors.

Comparison of text messaging and paper-and-pencil for ecological momentary assessment of food craving and intake

Electronic devices such as mobile phones are quickly becoming a popular way to gather participant reports of everyday thoughts, feelings, and behaviors, including food cravings and intake. Electronic devices offer a number of advantages over alternative methods such as paper-and-pencil (PNP) assessment including automated prompts, on-the-fly data transmission, and participant familiarity with and ownership of the devices. However, only a handful of studies have systematically compared compliance between electronic and PNP methods of ecological momentary assessment (EMA), and none have examined eating specifically. Existing comparisons generally find greater compliance for electronic devices than PNP, but there is variability in the results across studies that may be accounted for by differences across research domains. Here, we compared the two EMA methods in an unexamined domain - eating - in terms of response rate and response latency, and their sensitivity to individual difference variables such as body mass index (BMI). Forty-four participants were randomly assigned to report on their food craving, food intake, and hunger four times each day for 2 weeks using either a PNP diary (N = 19) or text messaging (TXT; N = 25). Response rates were higher for TXT than PNP (96% vs. 70%) and latencies were faster (29 min vs. 79 min), and response rate and latency were less influenced by BMI in the TXT condition than in the PNP condition. These results support the feasibility of using text messaging for EMA in the eating domain, and more broadly highlight the ways that research domain-specific considerations (e.g., the importance of response latency in measuring short-lived food craving) interact with assessment modality during EMA.

Smartphone-based hearing screening in noisy environments

It is important and recommended to detect hearing loss as soon as possible. If it is found early, proper treatment may help improve hearing and reduce the negative consequences of hearing loss. In this study, we developed smartphone-based hearing screening methods that can ubiquitously test hearing. However, environmental noise generally results in the loss of ear sensitivity, which causes a hearing threshold shift (HTS). To overcome this limitation in the hearing screening location, we developed a correction algorithm to reduce the HTS effect. A built-in microphone and headphone were calibrated to provide the standard units of measure. The HTSs in the presence of either white or babble noise were systematically investigated to determine the mean HTS as a function of noise level. When the hearing screening application runs, the smartphone automatically measures the environmental noise and provides the HTS value to correct the hearing threshold. A comparison to pure tone audiometry shows that this hearing screening method in the presence of noise could closely estimate the hearing threshold. We expect that the proposed ubiquitous hearing test method could be used as a simple hearing screening tool and could alert the user if they suffer from hearing loss.

Improving the accuracy and efficiency of respiratory rate measurements in children using mobile devices

The recommended method for measuring respiratory rate (RR) is counting breaths for 60 s using a timer. This method is not efficient in a busy clinical setting. There is an urgent need for a robust, low-cost method that can help front-line health care workers to measure RR quickly and accurately. Our aim was to develop a more efficient RR assessment method. RR was estimated by measuring the median time interval between breaths obtained from tapping on the touch screen of a mobile device. The estimation was continuously validated by measuring consistency (% deviation from the median) of each interval. Data from 30 subjects estimating RR from 10 standard videos with a mobile phone application were collected. A sensitivity analysis and an optimization experiment were performed to verify that a RR could be obtained in less than 60 s; that the accuracy improves when more taps are included into the calculation; and that accuracy improves when inconsistent taps are excluded. The sensitivity analysis showed that excluding inconsistent tapping and increasing the number of tap intervals improved the RR estimation. Efficiency (time to complete measurement) was significantly improved compared to traditional methods that require counting for 60 s. There was a trade-off between accuracy and efficiency. The most balanced optimization result provided a mean efficiency of 9.9 s and a normalized root mean square error of 5.6%, corresponding to 2.2 breaths/min at a respiratory rate of 40 breaths/min. The obtained 6-fold increase in mean efficiency combined with a clinically acceptable error makes this approach a viable solution for further clinical testing. The sensitivity analysis illustrating the trade-off between accuracy and efficiency will be a useful tool to define a target product profile for any novel RR estimation device.

Fusion of smartphone motion sensors for physical activity recognition

For physical activity recognition, smartphone sensors, such as an accelerometer and a gyroscope, are being utilized in many research studies. So far, particularly, the accelerometer has been extensively studied. In a few recent studies, a combination of a gyroscope, a magnetometer (in a supporting role) and an accelerometer (in a lead role) has been used with the aim to improve the recognition performance. How and when are various motion sensors, which are available on a smartphone, best used for better recognition performance, either individually or in combination? This is yet to be explored. In order to investigate this question, in this paper, we explore how these various motion sensors behave in different situations in the activity recognition process. For this purpose, we designed a data collection experiment where ten participants performed seven different activities carrying smart phones at different positions. Based on the analysis of this data set, we show that these sensors, except the magnetometer, are each capable of taking the lead roles individually, depending on the type of activity being recognized, the body position, the used data features and the classification method employed (personalized or generalized). We also show that their combination only improves the overall recognition performance when their individual performances are not very high, so that there is room for performance improvement. We have made our data set and our data collection application publicly available, thereby making our experiments reproducible.

Mobile phone-based syndromic surveillance system, Papua New Guinea

The health care system in Papua New Guinea is fragile, and surveillance systems infrequently meet international standards. To strengthen outbreak identification, health authorities piloted a mobile phone-based syndromic surveillance system and used established frameworks to evaluate whether the system was meeting objectives. Stakeholder experience was investigated by using standardized questionnaires and focus groups. Nine sites reported data that included 7 outbreaks and 92 cases of acute watery diarrhea. The new system was more timely (2.4 vs. 84 days), complete (70% vs. 40%), and sensitive (95% vs. 26%) than existing systems. The system was simple, stable, useful, and acceptable; however, feedback and subnational involvement were weak. A simple syndromic surveillance system implemented in a fragile state enabled more timely, complete, and sensitive data reporting for disease risk assessment. Feedback and provincial involvement require improvement. Use of mobile phone technology might improve the timeliness and efficiency of public health surveillance.

Improving compliance in remote healthcare systems through smartphone battery optimization

Remote health monitoring (RHM) has emerged as a solution to help reduce the cost burden of unhealthy lifestyles and aging populations. Enhancing compliance to prescribed medical regimens is an essential challenge to many systems, even those using smartphone technology. In this paper, we provide a technique to improve smartphone battery consumption and examine the effects of smartphone battery lifetime on compliance, in an attempt to enhance users' adherence to remote monitoring systems. We deploy WANDA-CVD, an RHM system for patients at risk of cardiovascular disease (CVD), using a wearable smartphone for detection of physical activity. We tested the battery optimization technique in an in-lab pilot study and validated its effects on compliance in the Women's Heart Health Study. The battery optimization technique enhanced the battery lifetime by 192% on average, resulting in a 53% increase in compliance in the study. A system like WANDA-CVD can help increase smartphone battery lifetime for RHM systems monitoring physical activity.

Development and validation of the Smartphone Addiction Inventory (SPAI)

Objective

The aim of this study was to develop a self-administered scale based on the special features of smartphone. The reliability and validity of the Smartphone Addiction Inventory (SPAI) was demonstrated.

Methods

A total of 283 participants were recruited from Dec. 2012 to Jul. 2013 to complete a set of questionnaires, including a 26-item SPAI modified from the Chinese Internet Addiction Scale and phantom vibration and ringing syndrome questionnaire. There were 260 males and 23 females, with ages 22.9±2.0 years. Exploratory factor analysis, internal-consistency test, test-retest, and correlation analysis were conducted to verify the reliability and validity of the SPAI. Correlations between each subscale and phantom vibration and ringing were also explored.

Results

Exploratory factor analysis yielded four factors: compulsive behavior, functional impairment, withdrawal and tolerance. Test–retest reliabilities (intraclass correlations  = 0.74–0.91) and internal consistency (Cronbach's α = 0.94) were all satisfactory. The four subscales had moderate to high correlations (0.56–0.78), but had no or very low correlation to phantom vibration/ringing syndrome.

Conclusion

This study provides evidence that the SPAI is a valid and reliable, self-administered screening tool to investigate smartphone addiction. Phantom vibration and ringing might be independent entities of smartphone addiction.

A smart phone-based pocket fall accident detection, positioning, and rescue system

We propose in this paper a novel algorithm as well as architecture for the fall accident detection and corresponding wide area rescue system based on a smart phone and the third generation (3G) networks. To realize the fall detection algorithm, the angles acquired by the electronic compass (ecompass) and the waveform sequence of the triaxial accelerometer on the smart phone are used as the system inputs. The acquired signals are then used to generate an ordered feature sequence and then examined in a sequential manner by the proposed cascade classifier for recognition purpose. Once the corresponding feature is verified by the classifier at current state, it can proceed to next state; otherwise, the system will reset to the initial state and wait for the appearance of another feature sequence. Once a fall accident event is detected, the user's position can be acquired by the global positioning system (GPS) or the assisted GPS, and sent to the rescue center via the 3G communication network so that the user can get medical help immediately. With the proposed cascaded classification architecture, the computational burden and power consumption issue on the smart phone system can be alleviated. Moreover, as we will see in the experiment that a distinguished fall accident detection accuracy up to 92% on the sensitivity and 99.75% on the specificity can be obtained when a set of 450 test actions in nine different kinds of activities are estimated by using the proposed cascaded classifier, which justifies the superiority of the proposed algorithm.

A mobile-phone-based breath carbon monoxide meter to detect cigarette smoking

INTRODUCTION

Mobile phones hold considerable promise for delivering evidence-based smoking cessation interventions that require frequent and objective assessment of smoking status via breath carbon monoxide (Breath CO) measurement. However, there are currently no commercially available mobile-phone-based Breath CO meters. We developed a mobile-phone-based Breath CO meter prototype that attaches to and communicates with a smartphone through an audio port. We then evaluated the reliability and the validity of Breath CO measures collected with the mobile meter prototype and assessed the usability and acceptability of the meter.

METHODS

Participants included 20 regular smokers (≥10 cigarettes/day), 20 light smokers (<10 cigarettes/day), and 20 nonsmokers. Expired air samples were collected 4 times from each participant: twice with the mobile meter and twice with a commercially available Breath CO meter.

RESULTS

Measures calculated by the mobile meter correlated strongly with measures calculated by the commercial meter (r = .96, p < .001). Additionally, the mobile meter accurately distinguished between smokers and nonsmokers. The area under the receiver-operating characteristic curve for the mobile meter was 94.7%, and the meter had a combined sensitivity and specificity of 1.86 at an abstinence threshold of ≤6 ppm. Responses on an acceptability survey indicated that smokers liked the meter and would be interested in using it during a quit attempt.

CONCLUSIONS

The results of our study suggest that a mobile-phone-based Breath CO meter is a reliable, valid, and acceptable device for distinguishing between smokers and nonsmokers.