A smart bathroom scale is presented in the paper. It is a classical bathroom scale enriched with the possibility of measuring a reflective photoplethysmographic (PPG) signal. To achieve such functionality an optical reflective transducer was developed. Its location in the scale platform was selected according to the anatomical structure of the foot and the typical procedure of weight measurement when using the scale. An electronic circuit for the sensor was designed and developed. Its performance was examined and compared with the commercial system. However, in the latter system, a plethysmographic signal was measured on the hand finger. This signal was utilized as an accurate timing synchronization one. Finally, we have shown preliminary results obtained due to performing measurements on a small group of healthy volunteers. Additionally, an algorithm for pulse rate estimation that could apply to such, relatively low-quality data was proposed.

In this paper, device construction and preliminary results for shower safety assistance are presented. The device allows monitoring of shower-taking persons without violating privacy and intimacy, while it has the ability to detect a persons entering and leaving the shower and detecting fall conditions. It allows better supervision of elders living independently at their locations.

There are many approaches to non-invasively deter-mine blood pressure. Among them there are methods based on utilizing pulse transit time measured by means of photoplethys-mography. The variability of the blood pressure drop between two measurement sensors placed along the artery and its dependence on the selected parameters describing the cardiovascular system is presented in the paper. This pressure drop modifies the pressure pulse propagation velocity, thus also value of PTT. The properties of four fiducial points on the radial and brachial arteries were analyzed. Publicly available simulation data were used for the analyses. The best results were achieved for the point defined by the maximum of the first derivative of the signal.

It is estimated that 13 % of population over 50 years old suffer from symptomatic or asymptomatic peripheral artery disease (PAD). Ankle-brachial index (ABI) is viewed as a useful parameter in diagnostics of peripheral arterial disease, however screening tests with usage of this method are not advised. Hypoxia causes increase in lactate values and decrease in blood glucose. We hypothesize that the deficit in blood supply to the muscles of the lower limbs will manifest itself in a lower blood glucose concentration, e.g. in the toe measurement compared to the reference measurement taken in the part of the body where the blood supply is normal or slightly worse. We proposed simple method for determining the foot-toe glucose index (FTGI) based on automatic measurement of glucose concentration in a blood sample. Obtained results suggest that proposed method is more sensitive than cuff/ultrasound doppler method.

Pulse Wave Velocity (PWV) is measured and utilized in many clinical applications. Recently, a wide research has been led to develop a cuff-less and continuous blood pressure method basing on PWV. However, in this application a decision on choosing an appropriate fiducial point of pulse wave (PW) waveform is necessary and substantial. It would allow to measure time parameters necessary to determine PWV. An influence of sampling frequency and other preprocessing algorithms on an accuracy of fiducial points determination are discussed in the paper.

An optoelectronic device enhancing a smart chair functionality is presented in the paper. Its essential purpose is a detection of a sitting person presence on the chair by means of detecting the vital signs. Additionally, it could be used for determining of clothes layer parameters useful in adjusting a system of a capacitive electrocardiography.

Capacitive electrocardiogram (CECG) tends to deliver basic cardiac signals without need to use traditional glued electrodes. In the paper analysis of possibility if the ECG derived respiratory waveforms out of the CECG.

In this paper the simple architecture of neural network for hand gesture classification was presented. The network classifies the previously calculated parameters of EMG signals. The main goal of this project was to develop simple solution that is not computationally complex and can be implemented on microprocessors in low-cost 3D printed prosthetic arms. As the part of conducted research the data set EMG signals corresponding to 5 different gestures was created. The accuracy of elaborated solution was 90% when applied real time on data sampled with 1kHz frequency and 75% when applied real time on data acquired and process directly on microprocessor with lower,100Hz sampling frequency.

In this paper the main aspects of mechanical design behind the low-cost prosthetic arm are presented. The fundamentals of a proper design has been defined to obtain functional 3D printed 5 degree of freedom (DOF) prosthesis. The designed prosthetic arm is a part of the hybrid interface with eye tracking movement control. The main focus was to create affordable but usable prosthesis which corresponds in size and weights to the human arm. The iterative process (starting from the final segment of the arm) was used to design fully functioning arm. All the elements were evaluated regarding total weight and the maximum load that can be carried by the arm. The result of this work is a prototype that weighs below 6kg and has a range of motion comparable to the human's arm. Final product is able to freely move an object of a total weight of 1 kg. All the mechanical parts of the designed arm were 3D printed which therefore presented construction can be adopted by people with different disabilities and (when connected to interfaces like EEG, EMG or eye tracking) provide support in everyday life activities.

A non-invasive and continuous blood pressure estimation could allow a better diagnosis and an earlier detection of various diseases. It could be performed using a photoplethysmography. However, it requires that a relation between blood pressure and pulse transit time is known. Eleven theoretical formulas were used in obtaining the simulated and noise free synthetic data. Then, they were utilized in validation of three, commonly used, formulas for blood pressure estimation. Finally, the best one was indicated.

In the paper a method of electrode's contact estimation in capacitive electrocardiogram (CECG) is presented. Proposed solution allows estimation of contact quality for each individual electrode. This enables construction of multi-electrode CECG systems, where electrode pairs can be selected on the basis of the individual electrode contact quality.

This paper describes the possibility of monitoring the progress of knowledge and skills acquisition by the students of radiology. It is achieved by an analysis of a visual attention distribution patterns during image-based tasks solving. The concept is to use the eye-tracking data to recognize the way how the radiographic images are read by recognized experts, radiography residents involved in the training program, and untrained users who graduated from biomedical engineering. The results of research presented in this paper support the usefulness of earlier elaborated eye metrics, Visual Attention Time Product VATP, for skills measurement when using Electronic Medical Record for CT images evaluation. Moreover, it appears that it is possible to differentiate the level of residents skills in radiology structures recognition. Presented methodology can also be utilized in other areas where operator performs image related tasks.

EDR is an interesting measuring technique that allows an indirect assessment of respiratory activity. This is an alternative solution to direct methods that are based on the measurement of air flow, which require a specialized sensor or even a system. However, due to inter-personal anatomical differences, the optimal ECG lead (placement of the electrodes) ensuring the best EDR signal quality is not fixed. An influence of ECG lead geometrical relation to the heart axis on the EDR signal quality has been examined in the paper. It was found that optimal electrodes position strongly differs between individuals. For each person there were at least few leads with high correlation with reference signal (over 0.8). They allowed for respiration frequency estimation with almost 100% accuracy.

Impedance properties of bath solution are compared. Any ingredient such as soap, shampoo or bathing salt changes bath-solution's electrical properties eg. impedance. We have measured and analysed influence of typical bathing ingredients on electrical properties of the solution. We investigate impedance changes over frequency range from 100Hz tu 100kHz as it is most applicable for person detection. Electrical properties of bath solution knowledge is essential for person detection and biosignal acquisition of bathing person.

In this paper the possibility of person identification based on biosignal is investigated. The work focus on the analysis of the changes in intervals between successive R-waves of electrocardiogram (ECG) recorded by wearable electronics in form of a necklaces. The main idea behind this project is to find efficient tool which may prevent sudden consciousness loss episodes or even sudden death episodes related to rapid temperature changes. Proposed method relays on the estimation of the RR interval changes in time with three approximation functions. Then, the identification of a person is performed based on the parameters of the utilized estimation functions.

In a smart home, health and well-being monitoring systems could be embedded in everyday devices providing a pervasive care. A home bathroom scale is an example of such a device, typically used to measure body weight and very often its composition (e.g. body water/fat percentage). In this paper, we analyzed a potential use of the bathroom scale to measure electrocardiogram (ECG) from electrodes located on the scale's tile. In particular we used both, simulations and real measurements to analyze the possibility of a such approach. We originally created a simple finite element model to analyze a role of a vector cardiogram projected on the foot-foot lead. We also analyzed results obtained during experiments in which took part (in total) 13 healthy volunteers. They were examined both, in sitting and standing positions. As a result we showed that the quality of the recorded ECG signal from feet is highly related to the electrical vector orientation of the individual's heart. We additionally compared the detected QRS complexes from hands-and feet-sampled ECG for sitting and standing positions. Results showed that for the sitting position the difference was only for 3.6% of all QRS complexes, while for standing one about 24.9%.

A novel touch sensor utilizing a body communication technology is presented in the paper. The proposed device accepts orders (gestures) only from a person wearing it. Moreover, when comparing it to a similar, however an optical one, it appears as a less power consumable. Preliminary results of its properties examination are presented and discussed. Additionally, the developed sensor allows to measure a human body the electrical passive parameters thus, aside it performs a basic functionality it also delivers additional information on the user.

Gesture sensors for mobile devices, which have a capability of distinguishing hand poses, require efficient and accurate classifiers in order to recognize gestures based on the sequences of primitives. Two methods of poses recognition for the optical linear sensor were proposed and validated. The Gaussian distribution fitting and Artificial Neural Network based methods represent two kinds of classification approaches. Three types of hand poses, differing in the number of fingers joined together, were investigated. The reflected light intensity pattern originated by hand located closely to the sensor was parameterized into 14 features. The change of reflection pattern originated by hand dislocation was reduced by application of two variable functions in the first of the methods. A one and two hidden layers topologies were considered in the neural network related approach. Both methods were designed with the use of a training set of samples and validated with another (testing) set. The results present the average poses recognition rate of 81.19% for Gaussian distribution fitting and 90.02% for ANN based method.

In this paper we propose to use temporal muscle contraction to perform certain actions. Method: The set of muscle contractions corresponding to one of three actions including “single-click”, “double-click” “click-n-hold” and “non-action” were recorded. After recording certain amount of signals, the set of five parameters was calculated. These parameters served as an input matrix for the neural network. Two-layer feedforward neural network with one hidden layer of 200 neurons was applied to classify gestures based on the input matrix. Results: The network was trained using the dataset consisted of 43 samples and then tested on the 34 samples dataset. All gestures from the test set were correctly classified.

In this paper we present the research conducted on synchronous measurements of biosignals. The experiment was conducted to evaluate the possibility of estimating vital signs based on eye tracking. Method: The eGlasses platform was used for acquisition of ECG, respiration rate, eye and pupil movement and blood pressure. Data were acquired in three 5 min. intervals during which a subject was performing certain tasks. The signals were filtered and resampled. The correlation between blood pressure, respiration and pupil dilation was calculated. Results: The measurements were conducted on 12 healthy volunteers. The obtained correlation coefficient was similar for all people and measurement positions. Conclusions: The electronic eyewear like eGlasses can be utilized to measure and process essential vital signs. Although some results are promising, estimating a value of blood pressure or hart rate based on data provided by eye tracking module requires some further studies.

Nearly 10% of all upper limb amputations concern the whole arm. It affects the mobility and reduces the productivity of such a person. These two factors can be restored by using prosthetics. However, the complexity of human arm makes restoring its basic functions quite difficult. When the osseointegration and/or targeted muscle reinnervation (TMR) are not possible, different modalities can be used to control the prosthesis. In this paper the usability of electromyography (EMG) signals for such a control is evaluated. Method: first, the types of operations performed by the prosthetic arm that could be handled by EMG module were defined. The raw EMG signal, corresponding to the predefined gesture, was acquired from the surface of trapezius muscle. The pattern recognition neural network was trained to classify gestures based on recorded RAW data. Results: The neural network was trained using 56 signals corresponding to performed gestures. Optimal performance was achieved for 29 training cycles. The network was tested using data set of 56 gestures. The designed network was tested on gestures recorded from 10 volunteers. The gestures were correctly classified with nearly 84% accuracy. Conclusions: The EMG analysis is a reliable modality when it comes to hybrid interfaces for control over prosthetic arm.

In this paper we present the possibility of using eGlasses eye tracking module as an extension for Scratch programming tool which is a visual programming language supporting computer skills learning. The main concept behind this project is to setup the interface for rapid interaction design. Eye tracking is a powerful tool for hands free communication but for that requires a dedicated software. This software is rarely tailored for a specific needs of a potential user. It means that people who wants to explore gaze driven computer interfaces often need to create their own eye tracking software or need to have certain computer skills to be able to go through the software development kit (SDK) provided by the eye tracker vendors. It makes designing interaction by gaze quite challenging. The eGlasses eye tracking module was used to extend sensor values available in Scratch by the information about pupil position, gaze position and eye opened/eye closed signal. In this paper we have tested if the gaze data acquired by the eGlasses are reliable and can be used as an input signal for rapid interaction design using Scratch. The whole interface was validated regarding the system usability score (SUS). The purpose of our work is to support disabled children and their therapists but also to give a chance to a wider community, without computational skills, to easily check they ideas for gaze based interaction. The results of conducted studies with the participation of volunteers give strong foundations to support this statement.

Two methods of object position and movement estimation in relation to the user of smart glasses were investigated. An active infrared and ultrasonic methods of the obstacle detection were presented and compared. Application of these methods depend on active transducers type (physical medium used), geometry and surface properties of detected objects and their movement direction and speed. In the article properties of both detectors were compared and applicability of both methods in mobile, battery operated environment such as eGlasses platform were compared.

In this paper we evaluated the possible application of a passive, optical sensor as an interface for human-smart glasses interactions. The designed proximity sensor is composed of set of photodiodes and the appropriate hardware and software components. First, experiments were performed for the estimations of such parameters as distance to an object, its width and velocity. Achieved results were satisfactory. Therefore, next, a set of static and dynamic hand gestures was proposed together with the related recognition method. The method was verified during experiments with volunteers. Experiments have shown that in appropriate lighting conditions it is possible to detect static and dynamic simple hand gestures using inexpensive and computationally efficient sensor. These features enable the use of such a sensor as one of the smart glasses interfaces.

This paper presents the algorithm for validation of electrodes locations for the thoracic impedance measurements. In particular the presented algorithm was designed to perform the telemetric sleep apnea monitoring. One of the problems, during the clinical tests of a developed device, was to preserve the repeatability of measurements. It strongly depended on the appropriate electrodes placement on the examined person's thorax. It seems that the developed software, which allows inspecting the electrodes localization, significantly increases a possibility of impedance based sleep apnea monitoring at home. In this article, the properties of the evaluation algorithm of electrodes placement accuracy are presented.

In this paper we investigate the effectiveness of the gaze interaction within near-to-eye display. The practical aspect of the paper is about combining an eye tracker with smart glasses. Presented research is related with the eGlasses project, which is focused on the development of an open platform in the form of multisensory electronic glasses and related interaction methods. One of the implemented interaction methods is the one based on eye tracking module. Both, the advantages and limitation of the method are discussed. We also considering the calibration free method of fixation points estimation within the near-to-eye display.

An influence of head movements on the gaze estimation accuracy when using a head mounted eye tracking system is discussed in the paper. This issue has been examined for a multi-display environment. It was found that head movement (rotation) to some extent does not influence on the gaze estimation accuracy seriously. Acceptable results were obtained when using eye-tracker to communicate with a computer via in two displays simultaneously.

In this paper we present a new human-computer interface for the quantitative measurement of blowing activities. The interface can measure the air flow and air pressure during the blowing activity. The measured values are stored and used to control the state of the graphical objects in the graphical user interface. In speech therapy children will find easier to play attractive therapeutic games than to perform repetitive and tedious, traditional blowing actions. Therefore, we also propose a set of games that can be used together with the blowing device. The paper focuses on the design of the interface, preliminary experiments and results. Additionally, fours blowing games are described.

Implicit interaction combined with object recognition techniques opens a new possibility for gathering data and analyzing user behavior for activity and context recognition. The electronic eyewear platform, eGlasses, is being developed, as an integrated and autonomous system to provide interactions with smart environment. In this paper we present a method for the interactions with the recognized objects that can be used for electronic eyewear. The design of the control node is presented. The control node is the extension of the power socket, equipped with a set of sensors and ZigBee communication interface. The node is used to control electronic objects through user interactions with a mobile device. The preliminary results are presented based on the Android mobile phone used to recognize controllable objects based on the captured image sequences.

This paper presents the basic ideas of eye and gaze tracking in multiple-display environment. The algorithm for display detection and identification is described as well as the rules for gaze interaction in multi display environment. The core of the method is to use special LED markers and eye and scene tracking glasses. Scene tracking camera registers markers position which is then represented as a cloud of points. Analyzing the mutual positions of detected points the algorithm estimates screen/displays position. Display number is assigned based on special information marker. Described project shows the possibility of hands free interaction in MDE. It also presents how to register visual attention when information is dispersed on several screens.

Diagnosis of obstructive sleep apnea usually involves polysomnographic analysis, which unfortunately requires overnight stay in a specialized clinic and is very uncomfortable for a patient. This paper describes the method and apparatus for recording a set of signals to detect sleep apnea. The device records the following signals simultaneously: three-channel ECG, respiratory functions, signals from the accelerometer, and snoring sounds. Measurements are carried out during the night, in the patient's home. Algorithm for automatic analysis of the data can be used to detect sleep apnea and hypopnea.

An example of an infra-red remote control device is presented in this paper. The device is equipped with additional medical diagnostic features for physiological and mental training. It is primarily a diagnostic health-care unit to support the elderly. To improve the acceptance of the device, the additional features are hidden in the shape of an ordinary, well-known device.