Vello Kukk

An implantable analyzer of bio-impedance dynamics: mixed signal approach

An on-chip implantable lock-in analyzer of variations of the electrical bio-impedance has been designed and pilot versions of the ASIC based analyzer have been fabricated and tested. A mixed signal approach, as the most suitable way for accomplishing a low voltage and low power ASIC for applications in portable and implantable devices for various biomedical applications, is discussed.

An implantable analyzer of bio-impedance dynamics: mixed signal approach [telemetric monitors]

An on-chip implantable lock-in analyzer of variations of the electrical bio-impedance has been designed, and pilot ASICs have been fabricated and tested. A mixed signal approach as the most suitable way for accomplishing a low-voltage and low-power ASIC for use in implantable devices for various biomedical applications is discussed in this paper.

Decomposition method of an electrical bio-impedance signal into cardiac and respiratory components

The paper presents a method for adaptive decomposition of an electrical bio-impedance (BI) signal into two components: cardiac and respiratory. The decomposition of a BI signal is not a trivial process because of the non-stationarity of the signal components and overlapping of their harmonic spectra. An application specific orthonormal basis (ASOB) was designed to solve the decomposition task using the Jacobi weighting function in the standard Gram-Schmidt process. The key element of the bio-impedance signal decomposer (BISD) is a model of the cardiac BI signal, which is constructed from the components of the ASOB and is intended for use in the BISD for on-line tracking of the cardiac BI signal. It makes it possible to separate the cardiac and respiratory components of the total BI signal in non-stationary conditions. In combination with the signal-shape locked loop (SSLL), the BISD allows us to decompose the BI signals with partially overlapping spectra. The proposed BISD based method is accomplished as a PC software digital system, but it is oriented towards applications in portable and stationary cardiac devices and in clinical settings.

Home Lab Kits for Introductory Course in Electrical Engineering

Design, implementation, and experience of application of HomeLabKits are described. HomeLabkit is a small box containing everything needed to perform labs in a courses related to introduction into electrical engineering. In addition to the kit, a student needs a computer with Internet connection only. Both power supply and data processing is performed over USB-connection. The paper describes content of kit, the labs for which the kit has been designed, software functions and experience of application during one and half year (3 semesters). The different categories of students have used the kit and also different modes of usage were tested. Very positive results have lead us to the decision to base labs on HomeLabKits only.

New concepts of automatic answer evaluation in competence based learning

This paper introduces current work with automatic evaluation that has been done to enable algorithms generating proper feedback according to the mistakes students have made. Learning environment using novel competence based approach has been used to implement those concepts and over the years data from different development steps has been collected that can be used to verify the benefits to students results of offered algorithm that mimics step-by-step student answering process.

Student forgetting model: Practical experience

This paper describes student memory model applied during one semester for control of learning activities in Electrical Engineering introductory course. All assignments include tasks of 128 levels of difficulty; transitions between them are controlled by a state machine. For any level achieved by a student in one session, exponential forgetting function is applied. Two different time constants are used for theoretical tests and lab experiments. Recalculation of level, time constant, and floor is applied after any successive session. Students accepted that model quickly and analysis of results showed that it really helped to implement ldquorepetitio est mater studiorumrdquo. In the paper we describe the model in more details and provide analysis of collected data.

Signal-Shape Locked Loop (SSLL) as an Adaptive Separator of Cardiac and Respiratory Components of Bio-Impedance Signal

The paper presents an on-line signal processing system for adaptive separation of two infra-low frequency signals: cardiac and respiratory bio-impedance (BI) signals, which are the time varying components of the total BI signal. The separation process of such signals as cardiac and respiratory BI components, is not a trivial filtering due to overlapping of spectra and non stationarity of these signals, and moreover, due to the infra-low frequency range. Therefore, advanced signal processing concepts and methods are needed to achieve the goal. The Signal-Shape Locked Loop (SSLL) concept was introduced to solve the task. Using this concept, it is possible to separate two (or more) independent signal components from the total input signal. Technical solution of the system is intended for applications in portable and implantable cardiac devices.

Competence-based approach to learning

This paper describes competence based approach to complete learning process. The learning process is fully web-based and can be completed without attending campus. It consists of small exercises and lab experiments. Automatic evaluation by stimulating student answering process is explained. Labs are supported by HomeLabKit, small box that contains everything needed to perform lab tasks and can be lent from university. After two years of using competence-based learning in real learning, a lot of information has been collected that can now be analyzed.

Student’s Behavior in Free Learning Environment and Formal Education System

The learning environment under discussion is free from deadlines or any other restriction of formal systems (no regular actions, including lectures). Instead, a student has access to a web-based learning environment where the basic element is a task which is connected to a set of low-level competences. Learning itself means activation of competences, automatically or manually, at lower or higher level and automatic processing of student’s answers. It is expected that reaction from the system is instant and so the student has discussion with a partner who is smart enough to motivate the learner. Such an environment produces quite different behavior from learners and new effects and problems appear.

An Adaptively Tunable Model of the Cardiac Signal for the Bio-Impedance Signal Decomposer (BISD)

The paper presents the further development of the bio- impedance signal decomposer (BISD) of the total bio-impedance (BI) signal to its cardiac and respiratory components. The Jacobi orthonormal polynomials based adaptively tunable model of the cardiac BI signal is proposed in the paper, which plays very important role in the decomposition task. The importance arises from the fact, that the BISD must be reliable and have to correct operate with signals taken from different persons, and in such cases, when the cardiac BI signal of a person is changing in time. For the proposed system the reliability significantly depends on the difference between the model of the cardiac signal and the real cardiac signal (the reference signal). The averaged through several periods version of the already separated cardiac BI signal is used as reference signal in the proposed algorithm for tuning the parameters of the cardiac BI signal model using a modified Newton adaptation algorithm. After the model is elaborated, the system separates the cardiac and the respiratory components more accurately by tracking the cardiac BI signal.