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High-end biomedical applications are a good target for specific- purpose system-on-chip (SoC) implementations. Human heart electrocardiogram (ECG) real-time monitoring and analysis is an immediate example with a large potential market. Today, the lack of scalable hardware platforms limits real-time analysis capabilities of most portable ECG analyze...
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... key point of these systems is to break up functions into parallel operations, thus speeding up execution and allowing individual cores to run at a lower frequency with respect to traditional monolithic processor cores. Technology today allows the integration of tens of cores onto the same silicon die, and we therefore designed a parallel system with up to 13 masters and 16 slaves Figure 3. Since we are targeting a platform of practical interest, we choose advanced industrial components [12]. ...
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... can be instantiated as both: shared-bus or crossbar (partial or full), thus allowing efficient interconnect design and providing flexible support for design space exploration and for platform scalability. In our first implementation, we target a shared bus to reduce system complexity ( Figure 3) and assess whether application requirements can already be met or not with this configuration. ...
Citations
... Wavelet analysis [11], Principal Component Analysis [15]- [17] and Linear interpolation [16], [18] are some of the most commonly used methods for ECG analysis for extracting either HR or RR [19]- [21]. The Pan Tompkins solution for QRS detection offers low-complexity characteristics, making it suitable for low-end portable devices [22]; therefore, it is integrated into our methodology. ...
... In order to extract the HR and RR, R-peak detection of the ECG signal is a common initial step, since it is needed for derivation of both the vital sign estimations. In this stage, the Pan Tompkins algorithm [12] is chosen as the most appropriate because it has been shown to offer low-complexity characteristics during QRS analysis examination [22]; therefore, it is suitable for portable devices. Pan Tompkins has two learning stages and one detection stage. ...
... Rpeak detection of the ECG signal is a common initial step for both the HR and RR extraction. In this stage, the well-known Pan-Tompkins algorithm [5] is chosen as the most appropriate since it has been shown to offer low-complexity characteristics during QRS analysis examination [6], making it suitable for portable devices. ...
Low-cost biosensors combined with low-cost portable devices can be very useful in time critical situations of mass casualties, when fast triage procedure must be attained. A methodology that uses ECG to derive the vital parameters (heart rate and respiratory rate) needed for the triage procedure is presented and it is aimed to leverage affordable low-cost equipment that can be easily utilized by urgent medical units or even volunteers in events of considerable number of injured civilians. The methodology relies on selected well-known and published algorithms for heart rate and respiratory rate derivation from a given ECG signal. It consists of methods for R-wave detection, kurtosis computation, smoothing, and finding peaks. The proposed approach is shown to offer a good trade-off between the accurate measurement of the parameters and their fast derivation. It has been evaluated by using a publicly available database. Its robustness is measured in terms of accuracy estimation, showing a sensitivity of 0.87 for heart rate and 0.74 for respiratory rate, a sensitivity of 0.76 considering the triage process and an average-case execution time of 0.02 seconds, making it suitable for real-time applications.
... One approach take from [15], uses a parallel architecture to implement the Pan Thompkins algorithm, ACF-based algorithm and Fast Fourier Transform to realtime. These algorithms cannot be processed in real-time; however the parallel architecture described by this work allows independent calculations to be executed simultaneously, which allows for higher sampling rates while meeting real-time constraints. ...
... In particular, the approach presented in [15] uses a parallel architecture of the ST200 DSP MCU which is composed of four cores. Each MCU core has its own private memory that is connected on a shared bus. ...
Microcontrollers, the brains of embedded systems, have found their way into every aspect of our lives including medical devices such as pacemakers. Pacemakers provide life supporting functions to people therefore it is critical for these devices to meet their timing constraints. This thesis examines the use of hardware co-processing to accelerate the calculation time associated with the critical tasks of a pacemaker. In particular, we use an FPGA to accelerate a microcontroller’s calculation time of the Kendall Tau Rank Correlation Coefficient algorithm. The Kendall Tau Rank Correlation Coefficient is a statistical measure that determines the pacemaker’s voltage level for heart stimulation. This thesis explores three different hardware distributions of this algorithm between an FPGA and a pacemaker’s microcontroller. The first implementation uses one microcontroller to establish the baseline performance of the system. The next implementation executes the entire Kendall Tau algorithm on an FPGA with varying degrees of parallelism. The final implementation of the Kendall Tau algorithm splits the computational requirements between the microcontroller and FPGA. This thesis uses these implementations to compare system-level issues such as power consumption and other tradeoffs that arise when using an FPGA for co-processing.
... La necesidad de acortar la distancia médico-paciente es muy clara en los escenarios mencionados. [12,13] 5. Cuidado en el hogar: el desarrollo de tecnología para el hogar ha tenido un alto crecimiento en los últimos tiempos. Pacientes que en casos regulares estarían obligados a permanecer en un centro de salud por periodos extensos, comienzan a tener otra opción. ...
Developing of wireless personal mobile systems and home automation have been in the mind of scientists and engineers for some decades. In recent years a huge variety of mobile systems that offer an increasing amount of applications for personal communication and productivity have been intro-duced in the market. That trend besides to the apparition of new sensors has allowed the developing of accessible personal telemedicine systems. This article proposes the developing of a Personal Monitoring and Alert System (spanish abbreviations SMyAP) for third age people. The goal of the system is to preserve the user independence, offering attention in emergen-cies produced for falls, abnormal or irregular bio-signals, etc. The SMyAP will be developed using open-source platforms and programming languages in new generation mobile sys-tems.
... La necesidad de acortar la distancia médico-paciente es muy clara en los escenarios mencionados. [12,13] 5. Cuidado en el hogar: el desarrollo de tecnología para el hogar ha tenido un alto crecimiento en los últimos tiempos. Pacientes que en casos regulares estarían obligados a permanecer en un centro de salud por periodos extensos, comienzan a tener otra opción. ...
Developing of wireless personal mobile systems and home automation have been in the mind of scientists and engineers for some decades. In recent years a huge variety of mobile systems that offer an increasing amount of applications for personal communication and productivity have been introduced in the market. That trend besides to the apparition of new sensors has allowed the developing of accessible personal telemedicine systems. This article proposes the developing of a Personal Monitoring and Alert System (spanish abbreviations SMyAP) for third age people. The goal of the system is to preserve the user independence, offering attention in emergencies produced for falls, abnormal or irregular bio-signals, etc. The SMyAP will be developed using open-source platforms and programming languages in new generation mobile systems.
... On the other hand, although most available DSP solutions (e.g. TI TMS320C54x [15] and ST220 [16] DSPs) offer both high-performance and power-efficiency, they cannot provide the application-specific customization beyond the DSP domain, demanded for adaptive medical processing. ...
In this paper we propose a multi-parameter reconfigurable architecture framework for patient-specific medical monitoring. This architecture is mainly composed of a set of heterogeneous processing engines and flexible communication interfaces, which enable the run-time configuration of the architecture for optimal diagnosis of different diseases. The flexibility of the proposed framework is evaluated by demonstrating two different medical applications for monitoring brain and heart status on an FPGA-based hardware prototype. The evaluated epileptic seizure detection application gains a high detection performance with overall accuracy of 98.52% and sensitivity of 99.47%. For the cardiac ICU monitoring application, the experimental results for detecting abnormality of blood pressure and heart rate in selected patients show a high true positive rate of 94.74%. By applying algorithmic enhancements in the detection scheme, we even achieve early detection of abnormalities in blood pressure in the range of few minutes before standard ICU monitor alarms with a true positive rate of 64%. With a balanced mixture of flexibility, patient-specificity, and detection accuracy at small hardware footprint, the proposed architecture can be an attractive framework for embedded monitoring of a wide variety of medical conditions.
... Thus, there is an increasing trend towards building customized gateway devices specifically tailored towards wearable bio-monitoring platforms. As an example , recently an application-specific multiprocessor system-onchip (MPSoC) design has been proposed for real-time analysis of a 12-lead ECG [5], which requires processing of twelve different signals from the patient's body. Following this line of development, we focus on processor customization [4] to support the computation demand placed on the gateway device by high-end bio-monitoring applications . ...
Wearable bio-monitoring applications require significant computation bandwidth. Processor customization is a major technology trend that can potentially satisfy computation requirement. In this paper, we apply processor customization to wearable bio-monitoring platforms and create systems with high performance. We choose Stretch customizable processor as the hardware platform where application-specific extension instructions are implemented in reconfigurable logic. Experimental results demonstrate that processor customization can return a performance gain of up to 5.2X.
This paper describes an automated solution for improving the design methodology of bio-medical applications on embedded platform devices with security and privacy guarantees. Besides typical design parameters, the need for security and privacy guarantees at the communication, software and hardware layers further extend the design space. Security and privacy features require expertise in evaluating and deploying solutions which are often specific to the individual application scenario. This makes these concerns hard to take into account in a typical hardware-software design process. We discuss how an existing design workflow can be extended to support the early detection of security and privacy issues, the selection of appropriate countermeasures and their effective integration. We consider the application scenario of continuous heart monitoring and analysis, through employing a Holter device. The design space exploration enacted by our methodology allows solving the conflicting requirements posed by security, software optimization, and hardware architectural parameters, in order to fine tune the overall system design and optimize the desired system metrics. We provide an experimental analysis of the proposed approach, showing a 3X decrease in design time, as well as demonstrating that quality assurance constraints are met.
Body-area sensor network or BAN-based health monitoring is increasingly becoming a popular alternative to traditional wired bio-monitoring techniques. However, most biomonitoring applications need continuous processing of large volumes of data, as a result of which both power consumption and computation bandwidth turn out to be serious constraints for sensor network platforms. This has resulted in a lot of recent interest in design methods, modeling and software analysis techniques specifically targeted towards BANs and applications running on them. In this paper we show that appropriate optimization of the application running on the communication gateway of a wireless BAN and accurate modeling of the microarchitectural details of the gateway processor can lead to significantly better resource usage and power savings. In particular, we propose a method for deriving the optimal order in which the different sensors feeding the gateway processor should be sampled, to maximize cache re-use. Our case study using a faint fall detection application - from the geriatric care domain - which is fed by a number of smart sensors to detect physiological and physical gait signals of a patient show very attractive energy savings in the underlying processor. Alternatively, our method can be used to improve the sampling frequency of the sensors, leading to higher reliability and better response time of the application.
