Design and Development of Smart Brain-Machine-Brain Interface (SBMIBI) for Deep Brain Stimulation and Other Biomedical Applications

Machine collaboration with the biological body/brain by sending electrical information back and forth is one of the leading research areas in neuro-engineering during the twenty-first century. Hence, Brain-Machine-Brain Interface (BMBI) is a powerful tool for achieving such machine-brain/body collaboration. BMBI generally is a smart device (usually invasive) that can record, store, and analyze neural activities, and generate corresponding responses in the form of electrical pulses to stimulate specific brain regions. The Smart Brain-Machine-Brain-Interface (SBMBI) is a step forward with compared to the traditional BMBI by including smart functions, such as in-electrode local computing capabilities, and availability of cloud connectivity in the system to take the advantage of powerful cloud computation in decision making. In this dissertation work, we designed and developed an innovative form of Smart Brain-Machine-Brain Interface (SBMBI) and studied its feasibility in different biomedical applications. With respect to power management, the SBMBI is a semi-passive platform. The communication module is fully passive—powered by RF harvested energy; whereas, the signal processing core is battery-assisted. The efficiency of the implemented RF energy harvester was measured to be 0.005%. One of potential applications of SBMBI is to configure a Smart Deep-Brain-Stimulator (SDBS) based on the general SBMBI platform. The SDBS consists of brain-implantable smart electrodes and a wireless-connected external controller. The SDBS electrodes operate as completely autonomous electronic implants that are capable of sensing and recording neural activities in real time, performing local processing, and generating arbitrary waveforms for neuro-stimulation. A bidirectional, secure, fully-passive wireless communication backbone was designed and integrated into this smart electrode to maintain contact between the smart electrodes and the controller. The standard EPC-Global protocol has been modified and adopted as the communication protocol in this design. The proposed SDBS, by using a SBMBI platform, was demonstrated and tested through a hardware prototype. Additionally the SBMBI was employed to develop a low-power wireless ECG data acquisition device. This device captures cardiac pulses through a non-invasive magnetic resonance electrode, processes the signal and sends it to the backend computer through the SBMBI interface. Analysis was performed to verify the integrity of received ECG data

Wireless Sensor System for Recycling

The motivation of this thesis was to research and design a prototype model of a wireless sensor network application, to be used as an automated detection infrastructure in recycling environment. The initial idea was to measure the level of the surface in a recycling container and transmit the information through a wireless communication system. The prototype is an initial step for recycling companies for building an automated detection network. Background of the research strongly supports the accomplished prototype. Study includes description of wireless environment with its problems and challenges. It proceeds with consideration of suitable wireless standards and considers most convenient sensor methods for recycling environment. Eventually document presents the prototype combining the studied entities. As a result, the prototype has two main operating parts: the wireless communication network and sensors. The network was realized with ZigBee standard by using two radio chips as communication nodes. Second communication node is attached to a recycling container and combined with two ultrasound sensors. This node includes a soft-ware algorithm, which is polling the state of the sensors regularly and deciding if the container is full. The node proceeds to transmission of the information to other communication node. This node is connected to computer and will transmit the information to be used by the recycling organization.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Supporting Cyber-Physical Systems with Wireless Sensor Networks: An Outlook of Software and Services

Sensing, communication, computation and control technologies are the essential building blocks of a cyber-physical system (CPS). Wireless sensor networks (WSNs) are a way to support CPS as they provide fine-grained spatial-temporal sensing, communication and computation at a low premium of cost and power. In this article, we explore the fundamental concepts guiding the design and implementation of WSNs. We report the latest developments in WSN software and services for meeting existing requirements and newer demands; particularly in the areas of: operating system, simulator and emulator, programming abstraction, virtualization, IP-based communication and security, time and location, and network monitoring and management. We also reflect on the ongoing efforts in providing dependable assurances for WSN-driven CPS. Finally, we report on its applicability with a case-study on smart buildings

Testbed Design and Implementation For Wireless Power Transfer Using Software Defined Radios

The area of wireless power transfer (WPT) dates back more than a century. This capability to transfer power without wires gives also motive for harvesting resources that have not yet been considered, such as the RF signals that cellular networks employ to send information. Only a while ago the research in the WPT field was focused on improving the elements in the power transmission chains separately. However, in recent years, such closed-loop schemes have emerged that have the potential to improve the efficiency of the entire system by adapting key elements in the chain together, such as the transmitted waveform and the rectenna performance. The scope of the thesis aims to contribute to the ultimate objective of merging information and power transfer in a simultaneous wireless information and power transfer/transmission (SWIPT) network. The main objective of this thesis is to design and implement a testbed for research on WPT and SWIPT. A closed-loop system is implemented for future scientific experiments for broadcasting a given radio signal and at the same time measuring the total power that an energy receiver will harvest from the transmission. The main element of the testbed is a computer from which master program controlling the transmission, the synchronization, and reading of the harvested voltage. The master program is written in C++ language and is designed to transmit with a USRP and receive voltage readings from the harvesting energy receivers that consist of RF-to-DC converter, ADC and Arduino microcontroller. Results show that the implemented testbed works as planned, and the master program can perform adaptive algorithms. Furthermore, the testbed can be used for experiments for any given waveform meant for communications, WPT, and SWIPT

Wireless Sensors and their Applications in Controlling Vibrations

As wireless devices are becoming more powerful, more flexible and less costly to produce, they are often being applied in new ways. Combining wireless technology with new types of sensors results in the ability to monitor and control the environment in ways not previously possible. For example, an intelligent wireless sensor system that consists of a sensor, digital processor and a transceiver can be mounted on a board the size of a coin. The data collected by these devices are then transmitted to a central unit which is able to thoroughly process and store this data. Not only can the central processing station provide reports about certain physical parameters in the environment, it can also control the environment and other parameters of interest. The design process of these wireless sensor platforms is a well-developed area of research that covers concepts like networking, circuit design, Radio-Frequency (RF) circuits and antenna design. The design of a wireless sensor can be as simple as putting together a microcontroller, a transceiver and a sensor chip or as complicated as implementing all the necessary circuitry into a single integrated circuit. One of the main applications of the sensors is in a control loop which controls physical characteristics in an environment. Specifically, if the objective of a control system is to limit the amount of vibrations in a structure, vibration sensors such as accelerometers are usually used. In environments where the use of wires is costly or impossible, it makes sense to use wireless accelerometers instead. Among the numerous applications that can use such devices are the automotive and medical vibration control systems. In the automotive industry it is desirable to reduce the amount of vibrations in the vehicle felt by the passengers. These vibrations can originate from the engine or the uneven road, but they are damped using passive mechanical elements like rubber, springs and shocks. It is possible however, to have a more effective vibration suppression using active sensor-actuator systems. Since adding and maintaining wires in a vehicle is costly, a wireless accelerometer can be put to good use there. A medical application for wireless accelerometers can be used with a procedure called Deep Brain Stimulation (DBS). DBS is a relatively new and very effective treatment for advanced Parkinson’s disease. The purpose of DBS is to reduce tremors in the patients. In DBS a set of voltages is applied to the brain of the patient as some optimum combinations of voltages will have a very positive effect on the tremors. Those optimum voltages are currently found by trial and error while a doctor is observing the patient for tremors. Wireless accelerometers with the use of a computer algorithm can assist in this process by finding the optimum voltages using the feedback provided by the accelerometers. The algorithm will assist the doctor in making decisions and has the potential of finding the optimums completely on its own

ZigBee-based Firmware Updating Algorithms in Smart Home Environment

Smart home system is comprised of two parts: the home gateway and a number of home appliances. ZigBee technology has great advantage (or IEEE 802.15.4) and is widely used in this system. Therefore, updating the smart home ZigBee firmware is essential in the practice. Since the ZigBee network contains massive nodes and many sensors are battery powered,resource-efficiency, multi-node concurrent congestion and other ZigBee nodes’ interference become challenges during the firmware updating. A lot of research has been done regarding updating optimizations for a single updating mode, such as firmware image compression algorithms and routing request strategies updating. Most optimizations are implemented in either wire or wireless updating avenue. However, there is a limited research on updating solution in combined wired and wireless methods. This dissertation proposes an integrated ZigBee network firmware updating solution scheme that uses the gateway to conduct the ZigBee network firmware updating by the wired method (Serial bootloader (SBL)) and the wireless method (Over-the-air (OTA)). Considering the ZigBee nodes’resourcelimitation,thisdissertationdesignsanimbleimagedecompressionalgorithm, namely Huffman Hamilton-circuit decompression (HHD) to optimize the ZigBee SBL wired updating. MATLAB simulations show that the decompression algorithm saves storage space and time, when compared to the traditional Huffman image compression. For wireless updating, a distributed priority page-request OTA (DPPOTA) algorithm is proposed which will reduce the OTA network data redundancy and duration of updating. This dissertation implements the DPPOTA, Optimization OTA (OOTA) and TI’s original OTA updating schemes on the NS2 simulator. The results show that the DPPOTA algorithm outperforms the OOTA and TI’s OTA. Compared with the related OTA optimization work, DPPOTA has a better performance on reducing network jitter and transmission delay. Under the different application scenarios, this dissertation proposes the combined updating solution which can exert the advantages of each single mode and outperforms any single mode

Wireless Sensors and their Applications in Controlling Vibrations

As wireless devices are becoming more powerful, more flexible and less costly to produce, they are often being applied in new ways. Combining wireless technology with new types of sensors results in the ability to monitor and control the environment in ways not previously possible. For example, an intelligent wireless sensor system that consists of a sensor, digital processor and a transceiver can be mounted on a board the size of a coin. The data collected by these devices are then transmitted to a central unit which is able to thoroughly process and store this data. Not only can the central processing station provide reports about certain physical parameters in the environment, it can also control the environment and other parameters of interest. The design process of these wireless sensor platforms is a well-developed area of research that covers concepts like networking, circuit design, Radio-Frequency (RF) circuits and antenna design. The design of a wireless sensor can be as simple as putting together a microcontroller, a transceiver and a sensor chip or as complicated as implementing all the necessary circuitry into a single integrated circuit. One of the main applications of the sensors is in a control loop which controls physical characteristics in an environment. Specifically, if the objective of a control system is to limit the amount of vibrations in a structure, vibration sensors such as accelerometers are usually used. In environments where the use of wires is costly or impossible, it makes sense to use wireless accelerometers instead. Among the numerous applications that can use such devices are the automotive and medical vibration control systems. In the automotive industry it is desirable to reduce the amount of vibrations in the vehicle felt by the passengers. These vibrations can originate from the engine or the uneven road, but they are damped using passive mechanical elements like rubber, springs and shocks. It is possible however, to have a more effective vibration suppression using active sensor-actuator systems. Since adding and maintaining wires in a vehicle is costly, a wireless accelerometer can be put to good use there. A medical application for wireless accelerometers can be used with a procedure called Deep Brain Stimulation (DBS). DBS is a relatively new and very effective treatment for advanced Parkinson’s disease. The purpose of DBS is to reduce tremors in the patients. In DBS a set of voltages is applied to the brain of the patient as some optimum combinations of voltages will have a very positive effect on the tremors. Those optimum voltages are currently found by trial and error while a doctor is observing the patient for tremors. Wireless accelerometers with the use of a computer algorithm can assist in this process by finding the optimum voltages using the feedback provided by the accelerometers. The algorithm will assist the doctor in making decisions and has the potential of finding the optimums completely on its own

Wireless sensor network as a distribute database

Wireless sensor networks (WSN) have played a role in various fields. In-network data processing is one of the most important and challenging techniques as it affects the key features of WSNs, which are energy consumption, nodes life circles and network performance. In the form of in-network processing, an intermediate node or aggregator will fuse or aggregate sensor data, which are collected from a group of sensors before transferring to the base station. The advantage of this approach is to minimize the amount of information transferred due to lack of computational resources. This thesis introduces the development of a hybrid in-network data processing for WSNs to fulfil the WSNs constraints. An architecture for in-network data processing were proposed in clustering level, data compression level and data mining level. The Neighbour-aware Multipath Cluster Aggregation (NMCA) is designed in the clustering level, which combines cluster-based and multipath approaches to process different packet loss rates. The data compression schemes and Optimal Dynamic Huffman (ODH) algorithm compressed data in the cluster head for the compressed level. A semantic data mining for fire detection was designed for extracting information from the raw data by the semantic data-mining model is developed to improve data accuracy and extract the fire event in the simulation. A demo in-door location system with in-network data processing approach is built to test the performance of the energy reduction of our designed strategy. In conclusion, the added benefits that the technical work can provide for in-network data processing is discussed and specific contributions and future work are highlighted