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.

The paper presents a multi-camera vision system designed for real-time applications. The system consists of six camera modules, which can be deployed at distances of up to approximately 15 meters from the central processing unit (host) without a significant loss in image quality. This configuration provides wide-angle coverage of the scene. The hardware design prioritizes cost-effectiveness and modularity. Each camera node is based, but not limited to, on the Raspberry Pi Camera Module 2, which integrates the Sony IMX219 CMOS sensor. The cameras were placed in enclosures that were self-designed and fabricated using 3D printing technology. The NVIDIA Jetson compute unit was used for image processing using artificial intelligence algorithms. This device enables the deployment of advanced computer vision models for real-time human pose estimation, such as YOLOv11 and OpenPose. Both frameworks are known for their high accuracy and low latency performance, making them suitable for time-sensitive applications. The use of on-device inference ensures efficient video data analysis while preserving low implementation costs and minimizing dependency on external processing infrastructure.

Peripheral artery disease (PAD), condition in which narrowed arteries reduce blood flow to the arms or legs It is estimated that 13% of the population over 50 years old suffers either from symptomatic or asymptomatic PAD. Ankle-brachial index (ABI) due to relatively low sensitivity and specificity is not recommended for screening. In this article we evaluate use of Active Dynamic Thermography as the alternative technique for the ischemia classification. By initially cooling the subject's tissue and then observing with a thermal camera, we were able to visualize vascularization and measure the tissue's ability to return to its initial state. Thermographic parameters obtained correspond well with age of the patient.

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.

In this paper, we summarize the results obtained from fire experiments. The aim of the work was to develop new methods of fire detection using IR thermal imaging cameras and dedicated image processing. We conducted 4 experiments in different configurations and with the use of different objects. The conducted experiments have shown the great usefulness of infrared cameras for detecting the seeds of a fire. Even cheap low-resolution bolometric detector modules can detect hot spots.

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 the paper, we summarize the evaluation of Anne4Care system after laboratory tests. A group of end users, seniors over 55 years of age, rated a virtual assistant by completing a questionnaire. The objectives of the pilot evaluations are mainly to assess the feasibility, usability, acceptance and functionality of the system and the ability of the potential target user to use the system and receive valuable information from it to help them address the complex needs of elderly people. The results of the assessment will be taken into account during further product development.

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.

In this preliminary study we, investigate the possibility of user recognition techniques suitable on smart home devices like chairs, beds, aiming for low-power, high accuracy and quick response time. We propose the two well know technique: voice speaker recognition and accelerometer signal from device mounted on the chair, and the third one optical system basing on IR LED transmitter/receiver circuit. The preliminary results proved that the developed system based on measurement and analysis of the accelerometer signal is very promising and suitable for implementation in the final product. The optical system requires further work but potentially it can be used for user identification purposes.

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%.

In the paper a modern approach to smart home heating is presented. Proposed solution utilizes at least two low-polluting energy source technologies. The main idea is to connect well known ecological energy sources in a way that they can support each other and minimize risks of failure when using single system or even both of them but managed in separate way. Considered energy technologies, used separatelly, have disadvantages, that can be reduced by smart interconnection between them. We are showing that adequately selecting supplementary energy sources can benefit in lower pollution and lower costs of system usage including higher reliability.

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.

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.

The paper presents an alternative approach to the monitoring of the cardiovascular system.The study depicts configurations of the utilized system and preliminary results of electrical and mechanical parameters of the cardiac system which can be measured using a head-worn device.

In this paper we describe possibility of use the RSSI signal (Radio Signal Strength Indication) from Texas Instruments SensorTag CC2650 for indoor positioning purposes.This idea is not a new but in our opinion it is possible to use SensorTags with Bluetooth LE wireless interface for positioning inside buildings in such applications as people findings in hospitals, senior come care, etc. RSSI is mostly selected as the sensor localization method in the indoor circumstances.In this paper, we aim to analyze accuracy, calibrate and map RSSI to distance by doing a series of the experiments.Obtained results are very promising and shows possibility of use this technique for position estimation.

A technique for the acquisition of an increased number of pupil positions, using a combined sensor consisting of a low-rate camera and a high-rate optical sensor, is presented in this paper.The additional data are provided by the optical movement-detection sensor mounted in close proximity to the eyeball.This proposed solution enables a significant increase in the number of registered fixation points and saccades and can be used in wearable electronics applications where low consumption of resources is required.The results of the experiments conducted here show that the proposed sensor system gives comparable results to those acquired from a high-speed camera and can also be used in the reduction of artefacts in the output signal.

Respiration rate is a very important vital sign.Different methods of respiration rate measurement or estimation have been developed.However, especially interesting are those that enable remote and unobtrusive monitoring.In this study, we investigated the use of smart glasses for the estimation of respiration rate especially useful for indoors applications.Two methods were analyzed.The first one is based on measurements of respiration-related body movements using an accelerometer.The second one uses the thermal camera to observe temperature changes in the nostril region.For both methods signals were extracted, filtered and processed using two different respiration rate estimators.Both methods were validated during experiments with the participation of volunteers using the respiration belt as a reference measurement method.Results proved that for both methods it is possible to reliable estimate the respiration rate with Root Mean Square Error lower than 2 breaths per minute, which is sufficient for medical screening.

In this preliminary study we analyzed the possibility of the reliable measurement of biomedical signals with some potential hardware extensions of smart glasses. Using specially designed experimental prototypes four category of biomedical signals were measured: electrocardiograms, electromyograms, electroencephalograms and respiration waveforms. Experiments with volunteers proved that using even simple construction of sensors it is possible to reliable measure biomedical signals with the quality enough for screening purposes as for the needs of simple interaction between an user and smart glasses.

In this paper we deal with the problem of precise gesture recognition for the active optical proximity sensor with sparse 8 photodiodes. We particularly focus on developing the method of estimating the real, usually not observable, maximum signal value representing maximum intensity of light reflected from an obstacle present in the front of the sensor. Different configurations of the fingers were used as an obstacle. The Monte Carlo simulations were performed in order to cognize the accurate pattern created by fingers of considered configurations. The accurate description of curves representing finger profiles was obtained after applying the least squares method. The results of analyzes proved that finger arrangement configurations, particularly 1 finger and 2 jointed fingers, can be considered as sources of Gaussian like shapes on the face of the sensor. Therefore, data measured by 8 sparse photodiodes of the active optical gesture sensor were compared to normal distribution curves. The results of the comparison allow normalization of the measured data and the estimation of the real, usually not observable, maximum signal value. The results and discussion sections of the paper present the average detection accuracy, advantages and limitations of the proposed approach.

In this paper we investigate the effectiveness of the interaction using eye tracking and electromyography. Smart glasses requires reliable interfaces for controlling the graphic content displayed directly in front of the user's eye. 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. The eye tracking provides quite accurate pointing but there is always a matter of how to select and confirm while using the eye tracking. In this paper we combine the eye tracking with the EMG signal acquired from the skeletal muscles. Both, the advantages and limitation of the method are discussed.

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.

In this study we evaluated system architecture for the use of smart glasses as a viewer of information, as a source of medical data (vital sign measurements: temperature, pulse rate, and respiration rate), and as a filter of healthcare information. All activities were based on patient/device identification procedures using graphical markers or features based on visual appearance. The architecture and particular use cases were implemented and verified using smart glasses prototypes developed under the eGlasses project and using a reference Health Level 7 Fast Healthcare Interoperability Resources (HL7 FHIR) server. The results show that information about the identified patient can be quickly retrieved from FHIR servers and annotated using voice recognition services. Smart glasses can be used in the measurement of vital signs of the observed patient, providing values of body temperature, pulse rate, and respiration rate by means of non-contact measurements. Such measurements are sufficiently reliable for medical screening and for fast data exchange using HL7 FHIR actions.

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.

Recently, different smart glasses solutions have been proposed on the market. The rapid development of this wearable technology has led to several research projects related to applications of smart glasses in healthcare. In this paper we propose a general architecture of the system enabling data integration for the recognized person. In the proposed system smart glasses integrates data obtained for the recognized patient from health care information systems, from devices connected to the patient and from the patient himself. The data integration is possible, if proper patient recognition procedure is used. Therefore, we evaluated three identification methods based on face recognition and using the recognition of graphical markers (i.e. QR-codes and proposed color-based codes). The results show that it is possible to obtain reliable and fast recognition results during the video acquisition by the smart glasses camera.

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.

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.