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.

This work describes the self-management support experience of the Patients with Dementia (PwD) at home by delivering a technology integrated model of assistance to the Informal Caregivers (ICs). Based on the conducted pilot tests the authors analyse, if non-invasive sensing technologies, are able to support the assistance management of the ICs, by delivering reliable information about deviations on usual behavioural patterns of PwD. The work presents the basic results of using Recurrent Neural Networks (RNN) in behaviour classification and anomaly detection at home.

The presented work describes a prototype (mockup) of a system for monitoring environmental parameters in residential and public premises. The developed system consists of a set of edge computing nodes aimed to collect sensor data that are sent to the server for further processing. On the example of single-board computers Raspberry Pi and BeagleBone we analyze the peculiarities of their use as edge computing nodes within one distributed system. The MQTT protocol facilitated data transmission between the server and the edge nodes. A specialized time series database, that is optimized for temporal data storage and processing, was utilized for storing the transmitted data. Grafana was employed for the collected data visualisation. The essential information, such as period averages, has been displayed as graphs on dashboards with help of created database queries. Additionally, a REST API was implemented to manage key objects and retrieve information, necessary from potential client applications. Based on the completed work and on the obtained data, we can conclude that the development of a system for controlling environmental indicators in residential and industrial premises, consisting of several edge computing nodes on the basis of different devices is possible, but when deciding on the design of such a system, it is required to consider the technical characteristics and configuration features of the used devices.

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.

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 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.

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.

A myriad of different electrical devices populate a typical household nowadays. Non-intrusive appliance load monitoring (NIALM) is an approach to find out how much energy each of them consumes in order to take measures to improve the overall energy efficiency. This article describes the ongoing research on improving electric loads recognition performed by NIALM algorithms within the context of smart homes and intelligent environments. The recognition performance can be significantly improved by decreasing the number of categories to be analyzed. The authors studied several labeling methods to categorize and group loads in order to increase the overall recognition rate. 31 different devices have been measured and labeled in different device states. Their input curves have been compared with 5 different machine learning algorithms. The best results could be reached by dividing all the loads into groups with small divergence in their normalized current curve. This approach has significantly increased the performance of NIALM recognition algorithms.

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.

The idea of applying semantic web technologies to the area of smart homes (SH) and building automation has resulted in a number of research activities and initiatives that have been recently developed. This article starts with an overview of ongoing work towards embedding semantics into home automation services. We then highlight the problems not considered by previous solutions. The core value of the work presented here is contained in a novel goal-driven approach for building automation service allocation and control. A new concept of semantic homes (SeH) and its architectural vision is another significant contribution. The comparison between existing and suggested solutions is rounded off by a use case scenario from the area of ambient assisted living.