Maciej KosNortheastern University | NEU · Personal Health Informatics
Maciej Kos
Ph.D Candidate | NIH NIA Doctoral Fellow
About
11
Publications
2,202
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40
Citations
Introduction
Additional affiliations
September 2015 - present
October 2014 - present
University of Michigan
Position
- Researcher
Publications
Publications (11)
Development of just-in-time adaptive health interventions requires reliable technologies for accurate monitoring of physiological parameters in ambulatory settings. Due to high heterogeneity of analytical methods used in evaluating heart rate (HR) sensors against electrocardiographs, harmonization of findings and comparison of sensors evaluated acr...
ABSTRACT
Microinteraction Ecological Momentary Assessment (uEMA) is a method for assessing affect in-situ using brief interactions. uEMA self-reports can be completed with a glance and a tap on an easily accessible wearable device, such as a smartwatch.
In prior work, despite an eight-times-higher sampling rate, uEMA, was shown to have higher re...
Availability of information is one of the most important factors for financial decision-makers. Having complete information about the probability of losing money should always leave decision-makers better off. However, in some situations financial decision-makers prefer to know less than more. In this study we investigated the impact of selected ch...
We developed an algorithm to clean RR data coming from wearable wrist PPG sensors. The algorithm uses Singular Spectrum Smoothing to generalize Poincare’s Method to more than one two dimensions. Our algorithm removes most motion artifacts and can be used to improve the quality of RR data.
A key prerequisite for precision medicine is the ability to assess metrics of human behavior objectively, unobtrusively and continuously. This capability serves as a framework for the optimization of tailored, just-in-time precision health interventions. Mobile unobtrusive physiological sensors, an important prerequisite for realizing this vision,...
To better approximate real-world learning and facilitate far-transfer, we varied the number of potential dimensions encoded in the stimulus used in a category learning task. Results suggest the difficulty of a categorization task - as reflected by individual and group-level measures of learning - depends on these.
In a cognitive training game (CTG), effective adjustment of difficulty parameters is critical for individually-optimized training. However, estimating the relative difficulty of disparate cognitive tasks in a CTG poses a challenge for investigators. Our research team has previously demonstrated how such estimation can be used to move from a partial...
The aim of the research was to identify the nature of the relationship between corporate reputation and individuals' investment decisions. We focused on three reputational factors that influence such decisions: value of stock market analysts' recommendation (either neutral or positive), reputation value (either positive or negative), and reputation...
When making financial decisions, decision-makers should perceive having complete risk information as beneficial. Surprisingly, in some situations decision-makers prefer to know less than more, even when it may result in losing money. Some shareholders do not keep themselves informed about the company they have invested in, and some online customers...
The poster shows results of a finacially incentivised exeriment on predictors of preventive bahaviours in the context of genetic health-risk information.
Projects
Project (1)
For the purpose of this project, we focus on risk information avoidance, by integrating our work with traditional normative and prescriptive models and recent findings about anticipatory emotions risk-as-feelings or feelings-as-information and the ‘new new economics of information’ literature. We plan to develop a powerful, highly generalizable framework for studying and interpreting consumer risk information avoidance across a variety of contexts and domains.
