Parsimonious System Identification from Fragmented Quantized Measurements.

Quantization is the process of mapping an input signal from an infinite continuous set to a countable set with a finite number of elements. It is a non-linear irreversible process, which makes the traditional methods of system identification no longer applicable. In this work, we propose a method for parsimonious linear time invariant system identification when only quantized observations, discerned from noisy data, are available.

The Specification of a Computational Model of Physical Activity Habit.

The influence of habit on physical activity is computationally modeled as the aggregated influence of past behavioral choices a person makes in a given context. We hypothesize that the influence of habit on behavior can be enhanced through engagement of the target behavior in a particular context or weakened through engagement of alternative behaviors in that context.

Assessing the impact of message relevance and frequency on physical activity change: A secondary data analysis from the random AIM trial.

Text messages are widely used to deliver intervention content; however, sending more intensive messages may not always improve behavioral outcomes. This study investigated whether message frequency was associated with daily physical activity, either by itself or in interaction with message content relevance. Healthy but insufficiently active young adults (aged 18-29 years) wore Fitbit activity trackers and received text messages for 180 days.

Physical Activity Dependence on Relative Temperature and Humidity Characteristics in a Young, Insufficiently Active Population: A Weather Typing Analysis.

Background: Physical activity (PA) is an important contributor to one's physical and mental health both acutely and across the lifespan. Much research has done on the ambient environment's impact on PA; however, these studies have used absolute values of atmospheric measures such as temperature and humidity, which vary spatiotemporally and make comparisons between studies which differ in location or time of year difficult to square with one another.

Methods: Here, we employ the Global Weather Type Classification, Version 2, to determine the combined impact of temperature and humidity on PA in a sample of insufficiently active young adults.

Lp Quasi-norm Minimization: Algorithm and Applications.

Sparsity finds applications in diverse areas such as statistics, machine learning, and signal processing. Computations over sparse structures are less complex compared to their dense counterparts and need less storage. This paper proposes a heuristic method for retrieving sparse approximate solutions of optimization problems via minimizing the quasi-norm, where .

Wearable device adherence among insufficiently-active young adults is independent of identity and motivation for physical activity.

Wearable devices are increasingly being integrated to improve prevention, chronic disease management and rehabilitation. Inferences about individual differences in device-measured physical activity depends on devices being worn long enough to obtain representative samples of behavior. Little is known about how psychological factors are associated with device wear time adherence.

Motivational Message Framing Effects on Physical Activity Dynamics in a Digital Messaging Intervention: Secondary Analysis.

Background: Digital smartphone messaging can be used to promote physical activity to large populations with limited cost. It is not clear which psychological constructs should be targeted by digital messages to promote physical activity. This gap presents a challenge for developing optimal content for digital messaging interventions.

Dose-response relations between the frequency of two types of momentary feedback prompts and daily physical activity.

Objective: Self-monitoring and behavioral feedback are widely used to help people monitor progress toward daily physical activity goals. Little information exists about the optimal dosing parameters for these techniques or if they are interchangeable in digital physical activity interventions. This study used a within-person experimental design to evaluate associations between the frequency of two different prompt types (one for each technique) and daily physical activity.

Broad versus narrow bandwidth measures of experienced automaticity for physical activity.

Physical activity is important for health, yet most young adults are insufficiently active. Physical activity is regulated in part, by habit, typically operationalised as automaticity. Little is known about the characteristics of automaticity, or whether broad bandwidth unidimensional measures of automaticity for physical activity are superior to narrower bandwidth multi- dimensional measures.

Physical Activity Dynamics During a Digital Messaging Intervention Changed After the Pandemic Declaration.

Background: The COVID-19 pandemic adversely impacted physical activity, but little is known about how contextual changes following the pandemic declaration impacted either the dynamics of people's physical activity or their responses to micro-interventions for promoting physical activity.

Purpose: This paper explored the effect of the COVID-19 pandemic on the dynamics of physical activity responses to digital message interventions.

Methods: Insufficiently-active young adults (18-29 years; N = 22) were recruited from November 2019 to January 2020 and wore a Fitbit smartwatch for 6 months.

Affective judgments, environmental determinants, and physical activity in emerging and young adults.

Objective: Affective judgements represent a promising target for promoting physical activity among adults. This study examined whether relations between affective judgments and physical activity are robust after adjusting for social, built, and natural environmental determinants.

Design: Prospective cross-sectional study with 173 adults (70.

Wayset-based guidance of multirotor aerial vehicles using robust tube-based model predictive control.

The present paper is concerned with the wayset-based guidance of underactuated multirotor aerial vehicles (MAVs). A hierarchical guidance and control structure is first established, in which the guidance is realized as a supervisory loop. The lower-level stabilizing attitude and position control laws are assumed to be available.

Dynamic models of stress-smoking responses based on high-frequency sensor data.

Self-reports indicate that stress increases the risk for smoking; however, intensive data from sensors can provide a more nuanced understanding of stress in the moments leading up to and following smoking events. Identifying personalized dynamical models of stress-smoking responses can improve characterizations of smoking responses following stress, but techniques used to identify these models require intensive longitudinal data. This study leveraged advances in wearable sensing technology and digital markers of stress and smoking to identify person-specific models of stress and smoking system dynamics by considering stress immediately before, during, and after smoking events.

Person-specific dose-finding for a digital messaging intervention to promote physical activity.

Objective: Digital messaging is an established method for promoting physical activity. Systematic approaches for dose-finding have not been widely used in behavioral intervention development. We apply system identification tools from control systems engineering to estimate dynamical models and inform decision rules for digital messaging intervention to promote physical activity.

Identification of switched autoregressive exogenous systems from large noisy datasets.

The article introduces novel methodologies for the identification of coefficients of switching autoregressive moving average with exogenous input systems and switched autoregressive exogenous linear models. We consider cases where system's outputs are contaminated by possibly large values of noise for both cases of measurement noise and process noise. It is assumed that only partial information on the probability distribution of the noise is available.

Ergodic opinion dynamics over networks: learning influences from partial observations.

In this paper we address the problem of inferring direct influences in social networks from partial samples of a class of opinion dynamics. The interest is motivated by the study of several complex systems arising in social sciences, where a population of agents interacts according to a communication graph. These dynamics over networks often exhibit an oscillatory behavior, given the stochastic effects or the random nature of the local interactions process.

Seasons, weather, and device-measured movement behaviors: a scoping review from 2006 to 2020.

Background: This scoping review summarized research on (a) seasonal differences in physical activity and sedentary behavior, and (b) specific weather indices associated with those behaviors.

Methods: PubMed, CINAHL, and SPORTDiscus were searched to identify relevant studies. After identifying and screening 1459 articles, data were extracted from 110 articles with 118,189 participants from 30 countries (almost exclusively high-income countries) on five continents.

Engineering Person-Specific Behavioral Interventions to Promote Physical Activity.

Physical activity is dynamic, complex, and often regulated idiosyncratically. In this article, we review how techniques used in control systems engineering are being applied to refine physical activity theory and interventions. We hypothesize that person-specific adaptive behavioral interventions grounded in system identification and model predictive control will lead to greater physical activity than more generic, conventional intervention approaches.

Temporal Dynamics of Treatment Receipt in a Text Message Intervention for Physical Activity: Single-Group, Within-Person Trial.

Background: Mobile technology has increased the reach of health behavior interventions but raised new challenges in assessing the fidelity of treatment receipt. Fidelity can be compromised if participant fatigue or burden reduces engagement, leading to missed or delayed treatments for just-in-time interventions.

Objective: This study aimed to investigate the temporal dynamics of text message receipt confirmations.

A fully distributed traffic allocation algorithm for nonconcave utility maximization in connectionless communication networks.

As IP video services have emerged to be the predominant Internet application, how to optimize the Internet resource allocation, while satisfying the quality of experience (QoE) for users of video services and other Internet applications becomes a challenge. This is because the QoE perceived by a user of video services can be characterized by a staircase function of the data rate, which is nonconcave and hence it is "hard" to find the optimal operating point. The work in this paper aims at tackling this challenge.

Personalized models of physical activity responses to text message micro-interventions: A proof-of-concept application of control systems engineering methods.

Objectives: The conceptual models underlying physical activity interventions have been based largely on differences between more and less active people. Yet physical activity is a dynamic behavior, and such models are not sensitive to factors that regulate behavior at a momentary level or how people respond to individual attempts at intervening. We demonstrate how a control systems engineering approach can be applied to develop personalized models of behavioral responses to an intensive text message-based intervention.

Evaluating the effect of smoking cessation treatment on a complex dynamical system.

Objective: To understand the dynamic relations among tobacco withdrawal symptoms to inform the development of effective smoking cessation treatments. Dynamical system models from control engineering are introduced and utilized to evaluate complex treatment effects. We demonstrate how dynamical models can be used to examine how distinct withdrawal-related processes are related over time and how treatment influences these relations.

Designing adaptive intensive interventions using methods from engineering.

Objective: Adaptive intensive interventions are introduced, and new methods from the field of control engineering for use in their design are illustrated.

Method: A detailed step-by-step explanation of how control engineering methods can be used with intensive longitudinal data to design an adaptive intensive intervention is provided. The methods are evaluated via simulation.