Zoltan Gingl

This paper presents a simple, lightweight, automatic calibration method for low-cost triaxial accelerometers, utilizing the Earth’s gravitational constant in various orientations. It can be easily implemented using only fixed-point arithmetic and can run on low-power microcontrollers for real-time measurements, making it practical for scenarios with limited data storage and computational power, such as actigraphy or IoT applications. The method offers ease of use by automatically detecting motionless intervals, eliminating the need for complex positioning techniques. The procedure detects resting states and calculates the corresponding three-dimensional mean acceleration values during the measurement. After appropriately selecting these mean values, a set of calibration points is formed and passed to a gradient-based optimization algorithm for iterative estimation of the calibration coefficients. Different metrics were used for verification and comparison with other methods, which were calculated through simulations and tests based on real measurements. The results show that, despite its lightweight nature, the method performs equally to more complex solutions. This article provides a thorough explanation of a novel method for collecting calibration points, the optimization algorithm, and the methods used for performance evaluation in a reproducible manner.

(1) Background and Goal: Several studies have investigated the association of sleep, diurnal patterns, and circadian rhythms with the presence and with the risk states of mental illnesses such as schizophrenia and bipolar disorder. The goal of our study was to examine actigraphic measures to identify features that can be extracted from them so that a machine learning model can detect premorbid latent liabilities for schizotypy and bipolarity. (2) Methods: Our team developed a small wrist-worn measurement device that collects and identifies actigraphic data based on an accelerometer. The sensors were used by carefully selected healthy participants who were divided into three groups: Control Group (C), Cyclothymia Factor Group (CFG), and Positive Schizotypy Factor Group (PSF). From the data they collected, our team performed data cleaning operations and then used the extracted metrics to generate the feature combinations deemed most effective, along with three machine learning algorithms for categorization. (3) Results: By conducting the training, we were able to identify a set of mildly correlated traits and their order of importance based on the Shapley value that had the greatest impact on the detection of bipolarity and schizotypy according to the logistic regression, Light Gradient Boost, and Random Forest algorithms. (4) Conclusions: These results were successfully compared to the results of other researchers; we had a similar differentiation in features used by others, and successfully developed new ones that might be a good complement for further research. In the future, identifying these traits may help us identify people at risk from mental disorders early in a cost-effective, automated way.

Objective . Recent studies in respiratory system impedance (Zrs) with single-frequency oscillometry have demonstrated the utility of novel intra-breath measures of Zrs in the detection of pathological alterations in respiratory mechanics. In the present work, we addressed the feasibility of extracting intra-breath information from Zrs data sets obtained with conventional oscillometry. Approach . Multi-frequency recordings obtained in a pulmonology practice were re-analysed to track the 11 Hz component of Zrs during normal breathing and compare the intra-breath measures to that obtained with a single 10 Hz signal in the same subjects. A nonlinear model was employed to simulate changes in Zrs in the breathing cycle. The values of resistance ( R ) and reactance ( X ) at end expiration and end inspiration and their corresponding differences (Δ R and Δ X ) were compared. Main results . All intra-breath measures exhibited similar mean values at 10 and 11 Hz in each subject; however, the variabilities were higher at 11 Hz, especially for Δ R and Δ X . The poorer quality of the 11 Hz data was primarily caused by the overlapping of modulation side lobes of adjacent oscillation frequencies. This cross-talk was enhanced by double breathing frequency components due to flow nonlinearities. Significance . Retrospective intra-breath assessment of large or special data bases of conventional oscillometry can be performed to better characterise respiratory mechanics in different populations and disease groups. The results also have implications in the optimum design of multiple-frequency oscillometry (avoidance of densely spaced frequencies) and the use of filtering procedures that preserve the intra-breath modulation information.

Modern instruments use sensors, analogue and digital electronics, and digital processing to measure almost any kind of physical quantities. Arduino is a very useful and widely used platform to build such systems in a school environment. Since it has analogue voltage inputs, it can be used as a digital voltmeter or even as a chart recorder. However, the ways of ensuring the required level of accuracy or just the right estimation of accuracy are often unknown or misunderstood. In this paper we try to fill this gap to aid reliable school experimentation.

A recent paper (Woong Sung Lee 2020 Phys. Educ. 55 023002) demonstrates how to build a low-cost Arduino-based system to measure temperature down to 77 K. The idea is interesting, and the paper has several merits, however we have found considerable mistakes. In our comment we point out what the problems are and show solutions too. We think that our analysis can help the reader to see what should be considered for proper operation and to see how the related methods can be useful concerning STEM education also. Our contribution can support reliable and accurate temperature measurement without calibration.

Műszaki informatikai szakmódszertan a modern oktatásban

The rapid evolution of intelligent electronic devices makes information technology, computer science and electronics strongly related to the teaching of natural sciences. Today almost everybody has a smart phone that can convert light, temperature, movement, sound to numbers, therefore all these can be processed, analysed, displayed, stored, shared by software applications. The fundamental question is how education can follow this knowledge and how can education take its advantages. Components and methods of modern technology are available for education also, teachers and students can play with parts and tools which were previously used only by engineers. A good example is the very popular Arduino board which is practically an industrial microcontroller whose pins are wired to easy-to-use connectors on a printed circuit board. In this paper we show a universal system which we have developed for the Arduino platform to support experimenting and understanding of the most fundamental principles of the operation of modern devices. We show our related educational concept and discuss the most important features of the system. Open source hardware and software are available and we provide a number of video tutorials as well.

Teaching about measurements and showing examples of instruments’ non-ideal behaviour are important in physics education. Digital multimeter input impedance analysis is perfect for this, since these instruments are easily available, precise enough, have good value/price ratio and represent modern technology. A recent paper (2018 Phys. Educ . 53 053005) demonstrates how the investigation of the input impedance of a digital multimeter can be used in education. However, we think that some more discussion is needed to make it more complete.

Small computer board platforms like Arduino, Raspberry Pi and micro:bit are very common, cheap and useful tools to teach modern technology, coding and experimenting in different disciplines at various levels. Due to the huge available information on websites it is very easy to find a solution for almost any job and problem, therefore one may not be motivated to work out an own version, to study carefully, to understand the principles in-depth and to be creative. This is also one of the reasons why so high proportion of the examples employ technically inadequate methods, misleading concepts. These are rather serious problems concerning high quality STEM (Science, Technology, Engineering and Mathematics) education. Although technology and available tools change rapidly, the basic principles remain the same, therefore education should focus on the better understanding of these. On the other hand, it is very important for the future’s engineers, developers, professionals to follow the correct methods, to be reliable, creative and open to the more and more common interdisciplinary methodology. In this paper we demonstrate this approach by investigating exciting interdisciplinary phonocardiography and photoplethysmography experiments and related electronics, data acquisition and signal processing. In our work we focus on the understanding and applying the correct methods, provide a detailed analysis of common pitfalls and leave room also for additional work. Students and teachers, lecturers can learn what to consider, pick what they find useful for their projects. It is also important to note, that the principles are valid for many other instrumentation and information processing jobs as well.