Browsing by Author "Özdemir, A. T."

Now showing 1 - 4 of 4

Open Access
Global vs local classification models for multi-sensor data fusion
(ACM, 2018) Pippa, E.; Zacharaki, E. I.; Özdemir, A. T.; Barshan, Billur; Megalooikonomou, V.
The aim of this paper is to investigate feature extraction and fusion of information across a number of sensors in different spatial locations to classify temporal events. Although the common feature-level fusion allows capturing spatial dependencies across sensors, the significant increase of feature vector dimensionality does not allow learning the classification models using a small number of samples usually available in practice. In decision-level fusion on the other hand, sensor-specific classification models are trained and subsequently integrated to reach a combined decision. Recent work has shown that decision-level fusion with a global (common for all sensors) classification model, is more appropriate for generalized events that show a (weak or strong) manifestation across all sensors. Although we can hypothesize that the choice of scheme depends on the event type (generalized vs focal/local), the prior work does not provide enough evidence to guide on the choice of fusion scheme. Thus in this work we aim to compare the three data fusion schemes for classification of generalized and non-generalized events using two case scenarios: (i) classification of paroxysmal events based on EEG patterns and (ii) classification of falls and activities of daily living (ADLs) from multiple sensors. The results support our hypothesis that feature level fusion is more beneficial for the characterization of heterogeneous data (based on an adequate number of samples), while sensor-independent classifiers should be selected in the case of generalized manifestation patterns.
Open Access
Investigation of sensor placement for accurate fall detection
(Springer, 2017) Ntanasis, P.; Pippa, E.; Özdemir, A. T.; Barshan, Billur; Megalooikonomou, V.
Fall detection is typically based on temporal and spectral analysis of multi-dimensional signals acquired from wearable sensors such as tri-axial accelerometers and gyroscopes which are attached at several parts of the human body. Our aim is to investigate the location where such wearable sensors should be placed in order to optimize the discrimination of falls from other Activities of Daily Living (ADLs). To this end, we perform feature extraction and classification based on data acquired from a single sensor unit placed on a specific body part each time. The investigated sensor locations include the head, chest, waist, wrist, thigh and ankle. Evaluation of several classification algorithms reveals the waist and the thigh as the optimal locations.
Open Access
One-step deposition of hydrophobic coatings on paper for printed-electronics applications
(Springer, 2019) Gözütok, Z.; Kinj, Ö.; Torun, İ.; Özdemir, A. T.; Önses, Mustafa Serdar
The ability to pattern highly conductive features on paper substrates is critically important for applications in radio frequency identification (RFID) tags, displays, sensors, printed electronics, and diagnostics. Ink-jet printing particle-free reactive silver inks is an additive, material efficient and versatile strategy for fabrication of highly conductive patterns; however, the intrinsic wetting properties of cellulose based papers are not suitable to serve as substrates for this process. This study reports one-step and practical modification of the surface of paper substrates using industrially available materials. The paper substrates were dip-coated with films of hydrocarbon and fluorocarbon based polymeric resins. Ink-jet printing particle-free reactive silver inks on the modified paper substrates followed by fast thermal annealing resulted in highly conductive patterns. The coatings improved the conductivity of the patterns and reduced the number of printing layers required to obtain conductivity. We finally demonstrated fabrication of a printed RFID tag on the coated paper substrates operating at the frequency range of 865–870 MHz.
Open Access
Rapid fabrication of high-performance transparent electrodes by electrospinning of reactive silver ink containing nanofibers
(Elsevier, 2020) Kiremitler, N. B.; Esidir, A.; Gözütok, Z.; Özdemir, A. T.; Önses, M. Serdar
All-solution processable fabrication of high performance transparent conductive electrodes is vital for next-generation optoelectronics applications. In this study, rapid and versatile fabrication of high-performance transparent electrodes by synergetic integration of electrospun nanofibers and particle-free reactive silver inks is reported. Direct electrospinning of reactive silver ink containing polymer blend solution followed by a swift thermal annealing enables fabrication of transparent conductive electrodes (TCEs) with a sheet resistance of ∼1.9 Ω/sq with 90% transmission. The high-performance TCEs were fabricated within couple of minutes including the electrospinning and thermal annealing duration. The key aspects of our strategy are the use of a polymer blend consisting of poly(ethylene oxide) (PEO) and polyvinylpyrrolidone (PVP) and particle-free nature of reactive silver inks. Practical utility of the fabricated transparent electrodes in Joule heaters that work at temperatures as high as 300 °C is presented. The simple, versatile, inexpensive, and rapid fabrication of transparent conductive electrodes can enable broad range of applications.