An orientation free adaptive step detection algorithm using a smart phone in physical activity monitoring

In this paper we present an Orientation Free Adaptive Step Detection (OFASD) algorithm for deployment in a smart phone for the purposes of physical activity monitoring. The OFASD algorithm detects individual steps and measures a user’s step counts using the smart phone’s in-built accelerometer. The algorithm considers both the variance of an individual’s walking pattern and the orientation of the smart phone. Experimental validation of the algorithm involved the collection of data from 10 participants using five phones (worn at five different body positions) whilst walking on a treadmill at a controlled speed for periods of 5 min. Results indicated that, for steps detected by the OFASD algorithm, there were no significant differences between where the phones were placed on the body (p > 0.05). The mean step detection accuracies ranged from 93.4 % to 96.4 %. Compared to measurements acquired using existing dedicated commercial devices, the results demonstrated that using a smart phone for monitoring physical activity is promising, as it adds value to an accepted everyday accessory, whilst imposing minimum interaction from the user. The algorithm can be used as the underlying component within an application deployed within a smart phone designed to promote self-management of chronic disease where activity measurement is a significant factor, as it provides a practical solution, with minimal requirements for user intervention and less constraints than current solutions.

Psychopathy and self-monitoring : additive and interactive effects on self-presentation tactics /

The purpose of this study was to determine the relative contributions of psychopathy and self-monitoring to the prediction of self-presentation tactics (behaviours that individuals use to manipulate their self-image). Psychopathy is composed of two main factors: Factor 1, which includes manipulativeness and shallow affect, and Factor 2, which includes irresponsibility and anti-social behaviours. Self-monitoring is a personality trait that distinguishes between those who adapt their behaviour to fit different social situations (high self-monitors) and those who behave as they feel regardless of social expectations (low selfmonitors). It was hypothesized that self-monitoring would moderate the relationship between psychopathy and self-presentation tactics. One hundred and forty-nine university students completed the Self-Monitoring Scale (Snyder, 1974), the Self-Report Psychopathy Scale - Version III (Paulhus et aI., in press), the Self-Presentation Tactics scale (Lee, S., et aI., 1999), the HEXACO-PI (a measure ofthe six major factors of personality; Lee, K., & Ashton, 2004), and six scenarios that were created as a supplementary measure of the selfpresentation tactics. Results of the hierarchical multiple regression analyses showed that self-monitoring did moderate the relationship between psychopathy and three of the selfpresentation tactics: apologies, disclaimers, and exemplification. Further, significant interactions were observed between Factor 1 and self-monitoring on apologies and the defensive tactics subscale, between Factor 2 and self-monitoring on self-handicapping, and between Factor 1 and Factor 2 on exemplification. Contrary to expectations, the main effect of self-monitoring was significant for the prediction of nine tactics, while psychopathy was significant for the prediction of seven tactics. This indicates that the role of these two personality traits in the explanation of self-presentation tactics tends to be additive in nature rather than interactive. In addition. Factor 2 alone did not account for a significant amount of variance in any of the tactics, while Factor 1 significantly predicted nine tactics. Results are discussed with regard to implications and possible directions for future research.

The effectiveness of a health versus appearance message on pregnant women's intentions to exercise postpartum : the moderating role of self-monitoring

Despite the confimied health benefits of exercise during the postpartum period, many new mothers are not sufficiently active. The present research aimed to examine the effectiveness of 2 types of messages on intention to exercise after giving birth on 2 groups of pregnant women (low and high self-monitors) using the Theory of Planned Behavior as a theoretical basis. Participants were 2 1 8 pregnant women 1 8 years of age and older (Mean age = 27.9 years, SD = 5.47), and in their second or third trimester. Women completed a demographics questionnaire, a self-monitoring (SM) scale and the Godin Leisure Time Exercise Questionnaire for current and pre-pregnancy exercise levels. They then read one of two brochures, describing either the health or appearance benefits of exercise for postpartum women. Women's attitudes, social norms, perceived behavioral control, and intentions to exercise postpartum were then assessed to determine whether one type of message (health or appearance) was more effective for each group. A MANOVA found no significant effect (p>0.05) for message type, SM, or their interaction. Possible reasons include the fact that the two messages may have been too similar, reading any message about exercise may result in intentions to exercise, or lack of attention given to the brochure. Given the lack of research in this area, more studies are necessary to confirm the present results. Two additional exploratory analyses were conducted. Pearson correlations found higher levels of pre-pregnancy exercise and current exercise to be associated with more positive attitudes, more positive subjective norms, higher perceived behavioral control, and higher intention to exercise postpartum. A hierarchical regression was conducted to determine the predictive utility of attitudes, subjective norms, and perceived behavioral control on intention for each self-monitoring group. Results of the analysis demonstrated the three independent variables significantly predicted intention (p < .001) in both groups, accounting for 58-62% of the variance in intention. For low self-monitors, attitude was the strongest predictor of intention, followed by perceived behavioral control and subjective norm. For high self-monitors, perceived behavioral control was the strongest predictors, followed by attitudes and subjective norm. The present study has practical and real world implications by contributing to our understanding of what types of messages, in a brochure format, are most effective in changing pregnant women's attitudes, subjective norm, perceived behavioral control and intention to exercise postpartum and provides ftirther support for the use of the Theory of Planned Behavior with this population.

A social-cognitive model of monitoring and its relationship to behaviour in a naturalistic observation : development and individual differences

years 8 months) and 24 older (M == 7 years 4 months) children. A Monitoring Process Model (MPM) was developed and tested in order to ascertain at which component process ofthe MPM age differences would emerge. The MPM had four components: (1) assessment; (2) evaluation; (3) planning; and (4) behavioural control. The MPM was assessed directly using a referential communication task in which the children were asked to make a series of five Lego buildings (a baseline condition and one building for each MPM component). Children listened to instructions from one experimenter while a second experimenter in the room (a confederate) intetjected varying levels ofverbal feedback in order to assist the children and control the component ofthe MPM. This design allowed us to determine at which "stage" ofprocessing children would most likely have difficulty monitoring themselves in this social-cognitive task. Developmental differences were obselVed for the evaluation, planning and behavioural control components suggesting that older children were able to be more successful with the more explicit metacomponents. Interestingly, however, there was no age difference in terms ofLego task success in the baseline condition suggesting that without the intelVention ofthe confederate younger children monitored the task about as well as older children. This pattern ofresults indicates that the younger children were disrupted by the feedback rather than helped. On the other hand, the older children were able to incorporate the feedback offered by the confederate into a plan ofaction. Another aim ofthis study was to assess similar processing components to those investigated by the MPM Lego task in a more naturalistic observation. Together the use ofthe Lego Task ( a social cognitive task) and the naturalistic social interaction allowed for the appraisal of cross-domain continuities and discontinuities in monitoring behaviours. In this vein, analyses were undertaken in order to ascertain whether or not successful performance in the MPM Lego Task would predict cross-domain competence in the more naturalistic social interchange. Indeed, success in the two latter components ofthe MPM (planning and behavioural control) was related to overall competence in the naturalistic task. However, this cross-domain prediction was not evident for all levels ofthe naturalistic interchange suggesting that the nature ofthe feedback a child receives is an important determinant ofresponse competency. Individual difference measures reflecting the children's general cognitive capacity (Working Memory and Digit Span) and verbal ability (vocabulary) were also taken in an effort to account for more variance in the prediction oftask success. However, these individual difference measures did not serve to enhance the prediction oftask performance in either the Lego Task or the naturalistic task. Similarly, parental responses to questionnaires pertaining to their child's temperament and social experience also failed to increase prediction oftask performance. On-line measures ofthe children's engagement, positive affect and anxiety also failed to predict competence ratings.

Uptake pathways: the potential of Bayesian belief networks to assist the management, monitoring and evaluation of development-orientated research

The effectiveness of development assistance has come under renewed scrutiny in recent years. In an era of growing economic liberalisation, research organisations are increasingly being asked to account for the use of public funds by demonstrating achievements. However, in the natural resources (NR) research field, conventional economic assessment techniques have focused on quantifying the impact achieved rather understanding the process that delivered it. As a result, they provide limited guidance for planners and researchers charged with selecting and implementing future research. In response, “pathways” or logic models have attracted increased interest in recent years as a remedy to this shortcoming. However, as commonly applied these suffer from two key limitations in their ability to incorporate risk and assess variance from plan. The paper reports the results of a case study that used a Bayesian belief network approach to address these limitations and outlines its potential value as a tool to assist the planning, monitoring and evaluation of development-orientated research.

Monitoring vegetation on railway embankments : supporting maintenance decisions

The national railway administrations in Scandinavia, Germany, and Austria mainly resort to manual inspections to control vegetation growth along railway embankments. Manually inspecting railways is slow and time consuming. A more worrying aspect concerns the fact that human observers are often unable to estimate the true cover of vegetation on railway embankments. Further human observers often tend to disagree with each other when more than one observer is engaged for inspection. Lack of proper techniques to identify the true cover of vegetation even result in the excess usage of herbicides; seriously harming the environment and threating the ecology. Hence work in this study has investigated aspects relevant to human variationand agreement to be able to report better inspection routines. This was studied by mainly carrying out two separate yet relevant investigations.First, thirteen observers were separately asked to estimate the vegetation cover in nine imagesacquired (in nadir view) over the railway tracks. All such estimates were compared relatively and an analysis of variance resulted in a significant difference on the observers’ cover estimates (p<0.05). Bearing in difference between the observers, a second follow-up field-study on the railway tracks was initiated and properly investigated. Two railway segments (strata) representingdifferent levels of vegetationwere carefully selected. Five sample plots (each covering an area of one-by-one meter) were randomizedfrom each stratumalong the rails from the aforementioned segments and ten images were acquired in nadir view. Further three observers (with knowledge in the railway maintenance domain) were separately asked to estimate the plant cover by visually examining theplots. Again an analysis of variance resulted in a significant difference on the observers’ cover estimates (p<0.05) confirming the result from the first investigation.The differences in observations are compared against a computer vision algorithm which detects the "true" cover of vegetation in a given image. The true cover is defined as the amount of greenish pixels in each image as detected by the computer vision algorithm. Results achieved through comparison strongly indicate that inconsistency is prevalent among the estimates reported by the observers. Hence, an automated approach reporting the use of computer vision is suggested, thus transferring the manual inspections into objective monitored inspections

A control chart based on sample ranges for monitoring the covariance matrix of the multivariate processes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A new chart based on sample variances for monitoring the covariance matrix of multivariate processes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A new chart for monitoring the covariance matrix of bivariate processes

In this article we consider a control chart based on the sample variances of two quality characteristics. The points plotted on the chart correspond to the maximum value of these two statistics. The main reason to consider the proposed chart instead of the generalized variance |S| chart is its better diagnostic feature, that is, with the new chart it is easier to relate an out-of-control signal to the variables whose parameters have moved away from their in-control values. We study the control chart efficiency considering different shifts in the covariance matrix. In this way, we obtain the average run length (ARL) that measures the effectiveness of a control chart in detecting process shifts. The proposed chart always detects process disturbances faster than the generalized variance |S| chart. The same is observed when the size of the samples is variable, except in a few cases in which the size of the samples switches between small size and very large size.

The Synthetic Control Chart Based on Two Sample Variances for Monitoring the Covariance Matrix

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Monitoring process mean and variability with one non-central chi-square chart

Traditionally, an (X) over bar -chart is used to control the process mean and an R-chart to control the process variance. However, these charts are not sensitive to small changes in process parameters. A good alternative to these charts is the exponentially weighted moving average (EWMA) control chart for controlling the process mean and variability, which is very effective in detecting small process disturbances. In this paper, we propose a single chart that is based on the non-central chi-square statistic, which is more effective than the joint (X) over bar and R charts in detecting assignable cause(s) that change the process mean and/or increase variability. It is also shown that the EWMA control chart based on a non-central chi-square statistic is more effective in detecting both increases and decreases in mean and/or variability.

Joint control charts for monitoring location and dispersion

The T-2 and the generalized variance vertical bar S vertical bar charts are used for monitoring the mean vector and the covariance matrix of multivariate processes. In this article, we propose for bivariate processes the use of the T-2 and the VMAX charts. The points plotted on the VMAX chart correspond to the maximum of the sample variances of the two quality characteristics. The reason to consider the VMAX statistic instead of the generalized variance vertical bar S vertical bar is the user's familiarity with the computation of simple sample variances; we can't say the same with regard to the computation of the generalized variance vertical bar S vertical bar.

Monitoring bivariate processes

The T2 chart and the generalized variance |S| chart are the usual tools for monitoring the mean vector and the covariance matrix of multivariate processes. The main drawback of these charts is the difficulty to obtain and to interpret the values of their monitoring statistics. In this paper, we study control charts for monitoring bivariate processes that only requires the computation of sample means (the ZMAX chart) for monitoring the mean vector, sample variances (the VMAX chart) for monitoring the covariance matrix, or both sample means and sample variances (the MCMAX chart) in the case of the joint control of the mean vector and the covariance matrix.

Structural damage detection in an aeronautical panel using analysis of variance

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Monitoring internal load parameters during simulated and official basketball matches

Moreira, A, McGuigan, MR, Arruda, AFS, Freitas, CG, and Aoki, MS. Monitoring internal load parameters during simulated and official basketball matches. J Strength Cond Res 26(3): 861-866, 2012-The purpose of this study was to compare the internal load responses (session rating of perceived exertion [RPE] and salivary cortisol) between simulated and official matches (SM and OM). Ten professional basketball players participated in 2 OMs and 2 SMs during the competition season. Subjects provided saliva samples 30 minutes before the prematch warm-up (PRE) and 10 minutes after the end of the match. Session RPE (CR-10 scale) was assessed 30 minutes after each match. The results from the 2-way analysis of variance showed significant differences for post-OM salivary cortisol as compared with pre-OM values (p < 0.05). No changes were observed for cortisol during the SM. Before the OM, a significant difference in salivary cortisol was observed as compared with pre-SM values (p < 0.05). Moreover, the OM session RPE was significantly greater than that of SM. There was a significant correlation between session RPE and cortisol changes (r = 0.75). In summary, the results of this study showed a greater magnitude of cortisol and session RPE responses after OM as compared with that after SM confirming the hypothesis that a real competition generates a greater stress response than a simulated condition does. The anticipatory effect was also observed in the OM. In addition, the results indicate that session RPE seems to be a viable tool in monitoring internal loads, and the results are useful in providing a better understanding of internal loads imposed by basketball training and competitions. The precise monitoring of these responses might help the coaches to plan appropriate loads maximizing recovery and performance.