Mobile patient simulator for resuscitation training with automatic external defibrillators

Resuscitation training has to be performed under most realistic conditions. This includes both usual CPR measures (breathing and chest compressions) and advanced measures, e.g. the usage of an Automatic External Defibrillator (AED). Almost all currently available simulators for ECG signals used in such trainings have a rather limited variety of available ECG signals. The trainer also has to change between different rhythms manually, resulting in a less realistic training environment. The development will result in mobile ECG simulator which can automatically react to events in the resuscitation process according to pre-programmed scenarios. It also has potential to simulate other physiological parameters like thorax impedance in the future.

Development of a current-controlled defibrillator for clinical tests

The work presented here is only a part of the development for a new current-controlled defibrillator. In the diploma thesis "Development and construction of a current-controlled defibrillator for clinical tests" the most important part was the control and safety of the defibrillator. To ensure a safe circuit design, a risk-analysis and a Failure Mode and Effects Analysis (FMEA) were necessary. Another major part was the programming of a microcontroller in embedded C and a programmable logic device in Very High Speed Integrated Circuit Description Language (VHDL). The circuit had to be constructed, and the defibrillator was optically decoupled from the laptop for safety reasons. The waveform-data can be transmitted to the microcontroller from the laptop, and the logged data is then transmitted back.

Recording and transmission of digital wound images with the help of a mobile device

The goal of this project is to develop a mobile device for transmitting images for the aftercare of surgical patients within the framework of the competence center TELTRA. After designing and evaluating different platforms and cameras, it was decided to develop for a compact flash camera card and an HSCSD modem which is based on and can be plugged into a pocket PC. The recorded images are sent with the help of a Java program from the pocket PC over an IrDA interface to the HSCSD mobile telephone, and then to the web server, where it is saved in a digital patient record.

Miniaturized module for the wireless transmission of measurements with Bluetooth

The wiring of patients for obtaining medical measurements has many disadvantages. In order to limit these, a miniaturized module was developed which digitalizes analog signals and sends the signal wirelessly to the receiver using Bluetooth. Bluetooth is especially suitable for this application because distances of up to 10 m are possible with low power consumption and robust transmission with encryption. The module consists of a Bluetooth chip, which is initialized in such a way by a microcontroller that connections from other bluetooth receivers can be accepted. The signals are then transmitted to the distant end. The maximum bit rate of the 23 mm x 30 mm module is 73.5 kBit/s. At 4.7 kBit/s, the current consumption is 12 mA.

The wireless monitoring of vital parameters: a design study

This project shows the way vital parameters can be transmitted and visualized with no connecting cables necessary to the PDA. This was realized using a sensor developed with an integrated Bluetooth interface and a PDA, also equipped with Bluetooth. This radio connection can span up to 10 m, and parameters, such as pulse frequency, oxygen saturation in blood, ECG measurements and plethysmograms, can be transmitted. Using the software introduced in this work, the transmitted measurements can be displayed numerically or graphically on the PDA. The software simultaneously checks for any limits and sends a warning message if these limits are exceeded. All received data are additionally documented.

Simulation methods for the online extraction of ECG parameters under Matlab/Simulink

The classification of cardiac pathologies in the human ECG greatly depends on the reliable extraction of characteristic features. This work presents a complete simulation environment for testing ECG classification algorithms under Matlab/Simulink. Evaluation of algorithm performance is undertaken in full compliance with the ANSI/AAMI standards EC38 and EC57, and ranges from beat-to-beat analysis to the comparison of episode markers (e.g., for VT/VF detection algorithms). For testing the quality of waveform boundary detection, our own testing methods have been implemented in compliance with existing literature.

Signalprocessing in transmission pulse hemometry

Supplying organs and body tissues with sufficient oxygen is one of the most important vital human functions. Commercial pulse oximeters compute the functional oxygen saturation from relative values (reduced hemoglobin and oxyhemoglobin). Methemoglobin (MetHb) and carboxyhemoglobin (COHb) are not taken into account, since they are considered to be reduced hemoglobin and oxyhemoglobin (RHb, HbO2). The total hemoglobin concentration is not included, and is determined by invasive methods. In this work, a non-invasive pulse oximeter is developed, which finds the entire hemoglobin concentration photometrically, and measures the fractional oxygen saturation and pulse rate. The signal of transmitted light I is processed according to the Lambert-Beer-law. The signal decays exponentially with the thickness d of the irradiated sample and its absorption coefficient alpha (I = I0 e -alpha d), where I0 is the incident light intensity.

Parameter extraction of ECG signals in real-time

In order for a mobile ECG recorder to be able to classify a heart rhythm online, the significant parameters must be extracted. The relevant parameters are the beginning, peak and end of the QRS-complex, the P- and T-waves, the ST-segment and other significant intervals, such as the RR-interval. The aim of the development was, firstly, stable, real-time-capable QRS detection, which finally achieved values for sensitivity of 98.9% and a positive predictivity of 99.9% on standard ECG databases. Also, a filter-based detection of P- and T-waves was implemented, which can also be performed in real-time on a microcontroller platform.

XML-based synchronization of mobile medical devices

Today, mobile computing provides enough resources to be used in medical applications. Patient treatment is a process that involves multiple partners. All those partners need access to common patient-data and need to make changes to the patients' health record. Therefore, data that the partners collect and change with mobile devices has to be synchronized on a central server to form the master patient record. Data conflicts resulting from the synchronization have to be solved automatically. Our project describes a solution for XML-based data replication and synchronization for mobile health applications.

Evaluation and optimization of different spectral estimation methods for EEG signals

The goal of this work was the evaluation of various spectral estimation methods with regard to their suitability for classifying EEG data. A test environment was implemented in which the algorithms are optimized and evaluated using various artificial and real EEG data. The methods are based on autoregressive approaches, as well as from FFT, wavelet, and matching pursuit-based spectral estimations. The evaluation showed that the quality of the results strongly correlate with the computational effort of the algorithm. The matching pursuit algorithm (MP) was implemented and further optimized since it had the best test result and had good scalability. Even under a sufficiently low runtime, it still gave good results.

Transmitting patient and device data via GSM--central management for decentral mobile medical devices

Equipping medical devices with long range telemetry opens completely new possibilities for emergency response, home care and remote diagnosis. Mobile communications nowadays seem to be a generally accepted part of our modern world, but bridging the gap between new (consumer-) technologies and medical devices still is a challenge today. Providing a telemetry link (GSM) is just the trivial part--ensuring security, reliability and service management are the more critical tasks that need to be addressed. Therefore, a complete system concept consists of an automatic fleet management (e.g. periodic device-initiated service calls) as well as customer relationship management (CRM), including technical service and a trouble-ticket system.

Automated sleep stage detection with a classical and a neural learning algorithm--methodological aspects

For classification tasks in biosignal processing, several strategies and algorithms can be used. Knowledge-based systems allow prior knowledge about the decision process to be integrated, both by the developer and by self-learning capabilities. For the classification stages in a sleep stage detection framework, three inference strategies were compared regarding their specific strengths: a classical signal processing approach, artificial neural networks and neuro-fuzzy systems. Methodological aspects were assessed to attain optimum performance and maximum transparency for the user. Due to their effective and robust learning behavior, artificial neural networks could be recommended for pattern recognition, while neuro-fuzzy systems performed best for the processing of contextual information.

[Development of Bluetooth wireless sensors]

Wireless communication could help to overcome current obstacles in medical devices and could enable medical services to offer completely new scenarios in health care. The Bluetooth technology which is the upcoming global market leader in wireless communication turned out to be perfectly suited not only for consumer market products but also in the medical environment [1]. It offers a low power, low cost connection in the medium range of 1-100 m with a bandwidth of currently 723.2 kbaud. This paper describes the development of a wireless ECG device and a Pulse Oximeter. Equipped with a Bluetooth port, the measurement devices are enabled to transmit data between the sensor and a Bluetooth-monitor. Therefore, CSR's Bluetooth protocol embedded two-processor and embedded single-processor architecture has been used.

Patient-dependent current dosing for semi-automatic external defibrillators (AED)

The improvements in semiconductors and modern circuitry allow new waveforms to be created for treating life-threatening heart fibrillation. A comparison of common waveforms shows that there is no definite optimal waveform. Especially in the case of early defibrillation by novices, the question of dosage should be re-discussed. While a physician may be able to dose the intensity of the therapeutic electric shock, one can't expect that from someone having no medical training. Common AEDs have predefined energy levels, that are delivered to a patient regardless of the patient's size and weight, etc. Current-based defibrillation provides a therapy matched to patient parameters, keeping the myocard stress as low as possible so that the heart has better chances of resuming a normal rhythm.

Kater-Karlsruhe Telemetry Test in Rescue Services

The Karlsruhe Telemetry Test in Rescue Services (KATER) investigates the central role of the regional emergency dispatch center as the midpoint of the emergency medicine information network using ECG telemetry, in order to be able to draw conclusions for future development. Rescue centers today form the logistic center of the flow of information. Expanding this legally formulated role to data flows within a network is just beginning, however, since the introduction of EDP in pre-clinical emergency medicine is still in the pilot project stage. Legislators are tending toward big solutions due to economic reasons. The increasing complexity of this problem can only be handled by a networked infrastructure.

Design aspects for novel, telemedical unattended diagnosis and therapy control systems for sleep disorders

Medical research confirmed the relevance of diagnosis and therapy of sleep-related breathing disorders, revealing prevalence and patho-physiological mechanisms [1-10]. Reliable sleep assessment currently demands examinations in the sleep-lab, which is very technical and time-consuming. Thus, expanding the conventional procedure to meet capacity demands does not seem realistic regarding cost aspects. As a solution, the authors present telemetric system concepts for the unattended assessment of a patient's sleep profile and cardio-respiratory parameters. Taking initial experience with home polysomnography into consideration, the presented research work focuses on easily applicable sensors, the corresponding sleep profile assessment rules, wireless data recording, intelligent signal processing algorithms and telemedical information logistics to include sleep-labs in the diagnosis and treatment process as competence centers.