92 research outputs found
Speech Enhancement using DWT for Hearing Aid Application
Hearing impairment is the number one chronic disability affecting people in the world. With a loss of hearing, person is restricted from his or her normal social activity, which may in turn cause undesirable influence on mental health. An effective treatment for the problem is hearing assistive device called hearing aid. With reference to patient’s audiogram hearing aid device would enhance signal such that hearing impaired person can hear comfortably. It has been tried to implement same technical concept. Presented approach for speech enhancement for hearing aid by using discrete wavelet transform-multiresolution analysis.
DOI: 10.17762/ijritcc2321-8169.150518
DIGITAL HEARING AID SIGNAL PROCESSING SYSTEM USING ANDROID PHONE
Objective: The objective of this research is to propose an Android-based digital hearing aid signal processing algorithm with following key features:(1) Regenerated audio match the patient-specific pattern of hearing loss, (2) noise reduction, and (3) provide flexibility to the users.Methods: The proposed signal processing algorithm is designed based on the specific hearing loss of the hearing disorder patient using inverse Fouriertransform; besides, noise reduction feature is included in the digital algorithm design as well. Proposed digital algorithm has been implemented intoan Android-based smartphone and its performance has been tested under real-time condition.Results: Simulation results show that the frequency response of the proposed digital hearing aid signal processing algorithm is in agreement withthe initial theoretical design that was carried out based on the hearing impaired patient’s audiogram. The proposed algorithm has been implementedin the Android-based smartphone and tested in real time. Results show that most of the patients are satisfied with the regenerated audio quality.According to patient’s comments, the regenerated audio is clear and the users are allowed to control the volume level. Besides, no obvious hearinglatency can be detected.Conclusion: Audio signals generated by the proposed digital signal processing algorithm show similar audio signal frequency response in boththeoretical design and MATLAB simulation results. The only difference between the design and simulation results is the amplification levels. Theproposed algorithm provides flexibility to the users by allowing them to choose the desired amplification level. In real-time testing, the proposedAndroid-based digital hearing aid is able to reduce noise level from the surrounding and the output processed speech match the patient-specifichearing loss
An optogenetic headstage for optical stimulation and neural recording in life science applications
L'optogénétique est une nouvelle méthode de contrôle de l’activité neuronale dans laquelle la lumière est employée pour activer ou arrêter certains neurones. Dans le cadre de ce travail, un dispositif permettant l’acquisition de signaux neuronaux et conduisant à une stimulation optogénétique de façon multicanale et temps-réel a été conçu. Cet outil est muni de deux canaux de stimulation optogénétique et de deux canaux de lecture des signaux neuronaux. La source de lumière est une DEL qui peut consommer jusqu’à 150 milliampères. Les signaux neuronaux acquis sont transmis à un ordinateur par une radio. Les dimensions sont d’environ 20×20×15 mm3 et le poids est de moins de 7 grammes, rendant l’appareil utile pour les expériences sur les petits animaux libres. Selon nos connaissances actuelles, le résultat de ce projet constitue le premier appareil de recherche optogénétique sans-fil, compact offrant la capture de signaux cérébraux et la stimulation optique simultanée.Optogenetics is a new method for controlling the neural activity where light is used to activate or silence, with high spatial and temporal resolution, genetically light-sensitized neurons. In optogenetics, a light source such as a LED, targets light-sensitized neurons. In this work, a light-weight wireless animal optogenetic headstage has been designed that allows multi-channel simultaneous real-time optical stimulation and neural recording. This system has two optogenetic stimulation channels and two electrophysiological reading channels. The optogenetic stimulation channels benefit from high-power LEDs (sinking 150 milliamps) with flexible stimulation patterns and the recorded neural data is wirelessly sent to a computer. The dimensions of the headstage are almost 20×20×15 mm3 and it weighs less than 7 grams. This headstage is suitable for tests on small freely-moving rodents. To the best of our knowledge, this is the first reported fully wireless headstage to offer simultaneous multichannel optical stimulation along with multichannel neural recording capability
Characterization of damage evolution on metallic components using ultrasonic non-destructive methods
When fatigue is considered, it is expected that structures and machinery eventually fail. Still, when this damage is unexpected, besides of the negative economic impact that it produces, life of people could be potentially at risk. Thus, nowadays it is imperative that the infrastructure managers, ought to program regular inspection and maintenance for their assets; in addition, designers and materials manufacturers, can access to appropriate diagnostic tools in order to build superior and more reliable materials. In this regard, and for a number of applications, non-destructive evaluation techniques have proven to be an efficient and helpful alternative to traditional destructive assays of materials. Particularly, for the design area of materials, in recent times researchers have exploited the Acoustic Emission (AE) phenomenon as an additional assessing tool with which characterize the mechanical properties of specimens. Nevertheless, several challenges arise when treat said phenomenon, since its intensity, duration and arrival behavior is essentially stochastic for traditional signal processing means, leading to inaccuracies for the outcome assessment.
In this dissertation, efforts are focused on assisting in the characterization of the mechanical properties of advanced high strength steels during under uniaxial tensile tests. Particularly of interest, is being able to detect the nucleation and growth of a crack throughout said test. Therefore, the resulting AE waves generated by the specimen during the test are assessed with the aim of characterize their evolution.
For this, on the introduction, a brief review about non-destructive methods emphasizing the AE phenomenon is introduced. Next is presented, an exhaustive analysis with regard to the challenge and deficiencies of detecting and segmenting each AE event over a continuous data-stream with the traditional threshold detection method, and additionally, with current state of the art methods. Following, a novel AE event detection method is proposed, with the aim of overcome the aforementioned limitations. Evidence showed that the proposed method (which is based on the short-time features of the waveform of the AE signal), excels the detection capabilities of current state of the art methods, when onset and endtime precision, as well as when quality of detection and computational speed are also considered. Finally, a methodology aimed to analyze the frequency spectrum evolution of the AE phenomenon during the tensile test, is proposed. Results indicate that it is feasible to correlate nucleation and growth of a crack with the frequency content evolution of AE events.Cuando se considera la fatiga de los materiales, se espera que eventualmente las estructuras y las maquinarias fallen. Sin embargo, cuando este daño es inesperado, además del impacto económico que este produce, la vida de las personas podría estar potencialmente en riesgo. Por lo que hoy en día, es imperativo que los administradores de las infraestructuras deban programar evaluaciones y mantenimientos de manera regular para sus activos. De igual manera, los diseñadores y fabricantes de materiales deberían de poseer herramientas de diagnóstico apropiadas con el propósito de obtener mejores y más confiables materiales. En este sentido, y para un amplio número de aplicaciones, las técnicas de evaluación no destructivas han demostrado ser una útil y eficiente alternativa a los ensayos destructivos tradicionales de materiales. De manera particular, en el área de diseño de materiales, recientemente los investigadores han aprovechado el fenómeno de Emisión Acústica (EA) como una herramienta complementaria de evaluación, con la cual poder caracterizar las propiedades mecánicas de los especímenes. No obstante, una multitud de desafíos emergen al tratar dicho fenómeno, ya que el comportamiento de su intensidad, duración y aparición es esencialmente estocástico desde el punto de vista del procesado de señales tradicional, conllevando a resultados imprecisos de las evaluaciones. Esta disertación se enfoca en colaborar en la caracterización de las propiedades mecánicas de Aceros Avanzados de Alta Resistencia (AAAR), para ensayos de tracción de tensión uniaxiales, con énfasis particular en la detección de fatiga, esto es la nucleación y generación de grietas en dichos componentes metálicos. Para ello, las ondas mecánicas de EA que estos especímenes generan durante los ensayos, son estudiadas con el objetivo de caracterizar su evolución. En la introducción de este documento, se presenta una breve revisión acerca de los métodos existentes no destructivos con énfasis particular al fenómeno de EA. A continuación, se muestra un análisis exhaustivo respecto a los desafíos para la detección de eventos de EA y las y deficiencias del método tradicional de detección; de manera adicional se evalúa el desempeño de los métodos actuales de detección de EA pertenecientes al estado del arte. Después, con el objetivo de superar las limitaciones presentadas por el método tradicional, se propone un nuevo método de detección de actividad de EA; la evidencia demuestra que el método propuesto (basado en el análisis en tiempo corto de la forma de onda), supera las capacidades de detección de los métodos pertenecientes al estado del arte, cuando se evalúa la precisión de la detección de la llegada y conclusión de las ondas de EA; además de, cuando también se consideran la calidad de detección de eventos y la velocidad de cálculo. Finalmente, se propone una metodología con el propósito de evaluar la evolución de la energía del espectro frecuencial del fenómeno de EA durante un ensayo de tracción; los resultados demuestran que es posible correlacionar el contenido de dicha evolución frecuencial con respecto a la nucleación y crecimiento de grietas en AAAR's.Postprint (published version
Computationally efficient algorithms and implementations of adaptive deep brain stimulation systems for Parkinson's disease
Clinical deep brain stimulation (DBS) is a tool used to mitigate pharmacologically intractable neurodegenerative diseases such as Parkinson's disease (PD), tremor and dystonia. Present implementations of DBS use continuous, high frequency voltage or current pulses so as to mitigate PD. This results in some limitations, among which there is stimulation induced side effects and shortening of pacemaker battery life. Adaptive DBS (aDBS) can be used to overcome a number of these limitations. Adaptive DBS is intended to deliver stimulation precisely only when needed. This thesis presents work undertaken to investigate, propose and develop novel algorithms and implementations of systems for adapting DBS. This thesis proposes four system implementations that could facilitate DBS adaptation either in the form of closed-loop DBS or spatial adaptation. The first method involved the use of dynamic detection to track changes in local field potentials (LFP) which can be indicative of PD symptoms. The work on dynamic detection included the synthesis of validation dataset using mainly autoregressive moving average (ARMA) models to enable the evaluation of a subset of PD detection algorithms for accuracy and complexity trade-offs. The subset of algorithms consisted of feature extraction (FE), dimensionality reduction (DR) and dynamic pattern classification stages. The combination with the best trade-off in terms of accuracy and complexity consisted of discrete wavelet transform (DWT) for FE, maximum ratio method (MRM) for DR and k-nearest neighbours (k-NN) for classification. The MRM is a novel DR method inspired by Fisher's separability criterion. The best combination achieved accuracy measures: F1-score of 97.9%, choice probability of 99.86% and classification accuracy of 99.29%. Regarding complexity, it had an estimated microchip area of 0.84 mm² for estimates in 90 nm CMOS process. The second implementation developed the first known PD detection and monitoring processor. This was achieved using complementary detection, which presents a hardware-efficient method of implementing a PD detection processor for monitoring PD progression in Parkinsonian patients. Complementary detection is achieved by using a combination of weak classifiers to produce a classifier with a higher consistency and confidence level than the individual classifiers in the configuration. The PD detection processor using the same processing stages as the first implementation was validated on an FPGA platform. By mapping the implemented design on a 45 nm CMOS process, the most optimal implementation achieved a dynamic power per channel of 2.26 μW and an area per channel of 0.2384 mm². It also achieved mean accuracy measures: Mathews correlation coefficient (MCC) of 0.6162, an F1-score of 91.38%, and mean classification accuracy of 91.91%. The third implementation proposed a framework for adapting DBS based on a critic-actor control approach. This models the relationship between a trained clinician (critic) and a neuro-modulation system (actor) for modulating DBS. The critic was implemented and validated using machine learning models, and the actor was implemented using a fuzzy controller. Therapy is modulated based on state estimates obtained through the machine learning models. PD suppression was achieved in seven out of nine test cases. The final implementation introduces spatial adaptation for aDBS. Spatial adaptation adjusts to variation in lead position and/or stimulation focus, as poor stimulation focus has been reported to affect therapeutic benefits of DBS. The implementation proposes dynamic current steering systems as a power-efficient implementation for multi-polar multisite current steering, with a particular focus on the output stage of the dynamic current steering system. The output stage uses dynamic current sources in implementing push-pull current sources that are interfaced to 16 electrodes so as to enable current steering. The performance of the output stage was demonstrated using a supply of 3.3 V to drive biphasic current pulses of up to 0.5 mA through its electrodes. The preliminary design of the circuit was implemented in 0.18 μm CMOS technology
An Energy-Efficient and Reliable Data Transmission Scheme for Transmitter-based Energy Harvesting Networks
Energy harvesting technology has been studied to overcome a limited power resource problem for a sensor network. This paper proposes a new data transmission period control and reliable data transmission algorithm for energy harvesting based sensor networks. Although previous studies proposed a communication protocol for energy harvesting based sensor networks, it still needs additional discussion. Proposed algorithm control a data transmission period and the number of data transmission dynamically based on environment information. Through this, energy consumption is reduced and transmission reliability is improved. The simulation result shows that the proposed algorithm is more efficient when compared with previous energy harvesting based communication standard, Enocean in terms of transmission success rate and residual energy.This research was supported by Basic Science Research Program through the National Research Foundation by Korea (NRF) funded by the Ministry of Education, Science and Technology(2012R1A1A3012227)
Cybersecurity in implantable medical devices
Mención Internacional en el título de doctorImplantable Medical Devices (IMDs) are electronic devices implanted within
the body to treat a medical condition, monitor the state or improve the
functioning of some body part, or just to provide the patient with a capability
that he did not possess before [86]. Current examples of IMDs
include pacemakers and defibrillators to monitor and treat cardiac conditions;
neurostimulators for deep brain stimulation in cases such as epilepsy
or Parkinson; drug delivery systems in the form of infusion pumps; and a
variety of biosensors to acquire and process different biosignals.
Some of the newest IMDs have started to incorporate numerous communication
and networking functions—usually known as “telemetry”—,
as well as increasingly more sophisticated computing capabilities. This
has provided implants with more intelligence and patients with more autonomy,
as medical personnel can access data and reconfigure the implant
remotely (i.e., without the patient being physically present in medical facilities).
Apart from a significant cost reduction, telemetry and computing
capabilities also allow healthcare providers to constantly monitor the patient’s
condition and to develop new diagnostic techniques based on an
Intra Body Network (IBN) of medical devices [25, 26, 201].
Evolving from a mere electromechanical IMD to one with more advanced
computing and communication capabilities has many benefits but
also entails numerous security and privacy risks for the patient. The majority
of such risks are relatively well known in classical computing scenarios,
though in many respects their repercussions are far more critical in the case
of implants. Attacks against an IMD can put at risk the safety of the patient
who carries it, with fatal consequences in certain cases. Causing an intentional
malfunction of an implant can lead to death and, as recognized by the
U.S. Food and Drug Administration (FDA), such deliberate attacks could
be far more difficult to detect than accidental ones [61]. Furthermore, these
devices store and transmit very sensitive medical information that requires
protection, as dictated by European (e.g., Directive 95/46/ECC) and U.S.
(e.g., CFR 164.312) Directives [94, 204].
The wireless communication capabilities present in many modern IMDs
are a major source of security risks, particularly while the patient is in open
(i.e., non-medical) environments. To begin with, the implant becomes no
longer “invisible”, as its presence could be remotely detected [48]. Furthermore,
it facilitates the access to transmitted data by eavesdroppers who
simply listen to the (insecure) channel [83]. This could result in a major privacy breach, as IMDs store sensitive information such as vital signals,
diagnosed conditions, therapies, and a variety of personal data (e.g., birth
date, name, and other medically relevant identifiers). A vulnerable communication
channel also makes it easier to attack the implant in ways similar
to those used against more common computing devices [118, 129, 156],
i.e., by forging, altering, or replying previously captured messages [82].
This could potentially allow an adversary to monitor and modify the implant
without necessarily being close to the victim [164]. In this regard,
the concerns of former U.S. vice-president Dick Cheney constitute an excellent
example: he had his Implantable Cardioverter Defibrillator (ICD)
replaced by another without WiFi capability [219].
While there are still no known real-world incidents, several attacks on
IMDs have been successfully demonstrated in the lab [83, 133, 143]. These
attacks have shown how an adversary can disable or reprogram therapies
on an ICD with wireless connectivity, and even inducing a shock state to
the patient [65]. Other attacks deplete the battery and render the device
inoperative [91], which often implies that the patient must undergo a surgical
procedure to have the IMD replaced. Moreover, in the case of cardiac
implants, they have a switch that can be turned off merely by applying a
magnetic field [149]. The existence of this mechanism is motivated by the
need to shield ICDs to electromagnetic fields, for instance when the patient
undergoes cardiac surgery using electrocautery devices [47]. However, this
could be easily exploited by an attacker, since activating such a primitive
mechanism does not require any kind of authentication.
In order to prevent attacks, it is imperative that the new generation of
IMDs will be equipped with strong mechanisms guaranteeing basic security
properties such as confidentiality, integrity, and availability. For example,
mutual authentication between the IMD and medical personnel is
essential, as both parties must be confident that the other end is who claims
to be. In the case of the IMD, only commands coming from authenticated
parties should be considered, while medical personnel should not trust any
message claiming to come from the IMD unless sufficient guarantees are
given.
Preserving the confidentiality of the information stored in and transmitted
by the IMD is another mandatory aspect. The device must implement
appropriate security policies that restrict what entities can reconfigure the
IMD or get access to the information stored in it, ensuring that only authorized
operations are executed. Similarly, security mechanisms have to
be implemented to protect the content of messages exchanged through an insecure wireless channel.
Integrity protection is equally important to ensure that information has
not been modified in transit. For example, if the information sent by the
implant to the Programmer is altered, the doctor might make a wrong decision.
Conversely, if a command sent to the implant is forged, modified,
or simply contains errors, its execution could result in a compromise of the
patient’s physical integrity.
Technical security mechanisms should be incorporated in the design
phase and complemented with appropriate legal and administrative measures.
Current legislation is rather permissive in this regard, allowing the
use of implants like ICDs that do not incorporate any security mechanisms.
Regulatory authorities like the FDA in the U.S or the EMA (European
Medicines Agency) in Europe should promote metrics and frameworks for
assessing the security of IMDs. These assessments should be mandatory
by law, requiring an adequate security level for an implant before approving
its use. Moreover, both the security measures supported on each IMD
and the security assessment results should be made public.
Prudent engineering practices well known in the safety and security domains
should be followed in the design of IMDs. If hardware errors are
detected, it often entails a replacement of the implant, with the associated
risks linked to a surgery. One of the main sources of failure when treating
or monitoring a patient is precisely malfunctions of the device itself.
These failures are known as “recalls” or “advisories”, and it is estimated
that they affect around 2.6% of patients carrying an implant. Furthermore,
the software running on the device should strictly support the functionalities
required to perform the medical and operational tasks for what it was
designed, and no more [66, 134, 213].
In Chapter 1, we present a survey of security and privacy issues in
IMDs, discuss the most relevant mechanisms proposed to address these
challenges, and analyze their suitability, advantages, and main drawbacks.
In Chapter 2, we show how the use of highly compressed electrocardiogram
(ECG) signals (only 24 coefficients of Hadamard Transform) is enough
to unequivocally identify individuals with a high performance (classification
accuracy of 97% and with identification system errors in the order of
10−2). In Chapter 3 we introduce a new Continuous Authentication scheme
that, contrarily to previous works in this area, considers ECG signals as
continuous data streams. The proposed ECG-based CA system is intended
for real-time applications and is able to offer an accuracy up to 96%, with
an almost perfect system performance (kappa statistic > 80%). In Chapter 4, we propose a distance bounding protocol to manage access control of
IMDs: ACIMD. ACIMD combines two features namely identity verification
(authentication) and proximity verification (distance checking). The
authentication mechanism we developed conforms to the ISO/IEC 9798-2
standard and is performed using the whole ECG signal of a device holder,
which is hardly replicable by a distant attacker. We evaluate the performance
of ACIMD using ECG signals of 199 individuals over 24 hours,
considering three adversary strategies. Results show that an accuracy of
87.07% in authentication can be achieved. Finally, in Chapter 5 we extract
some conclusions and summarize the published works (i.e., scientific
journals with high impact factor and prestigious international conferences).Los Dispositivos Médicos Implantables (DMIs) son dispositivos electrónicos
implantados dentro del cuerpo para tratar una enfermedad, controlar
el estado o mejorar el funcionamiento de alguna parte del cuerpo, o simplemente
para proporcionar al paciente una capacidad que no poseía antes
[86]. Ejemplos actuales de DMI incluyen marcapasos y desfibriladores
para monitorear y tratar afecciones cardíacas; neuroestimuladores para la
estimulación cerebral profunda en casos como la epilepsia o el Parkinson;
sistemas de administración de fármacos en forma de bombas de infusión; y
una variedad de biosensores para adquirir y procesar diferentes bioseñales.
Los DMIs más modernos han comenzado a incorporar numerosas funciones
de comunicación y redes (generalmente conocidas como telemetría)
así como capacidades de computación cada vez más sofisticadas. Esto
ha propiciado implantes con mayor inteligencia y pacientes con más autonomía,
ya que el personal médico puede acceder a los datos y reconfigurar
el implante de forma remota (es decir, sin que el paciente esté
físicamente presente en las instalaciones médicas). Aparte de una importante
reducción de costos, las capacidades de telemetría y cómputo también
permiten a los profesionales de la atención médica monitorear constantemente
la condición del paciente y desarrollar nuevas técnicas de diagnóstico
basadas en una Intra Body Network (IBN) de dispositivos médicos
[25, 26, 201].
Evolucionar desde un DMI electromecánico a uno con capacidades de
cómputo y de comunicación más avanzadas tiene muchos beneficios pero
también conlleva numerosos riesgos de seguridad y privacidad para el paciente.
La mayoría de estos riesgos son relativamente bien conocidos en los
escenarios clásicos de comunicaciones entre dispositivos, aunque en muchos
aspectos sus repercusiones son mucho más críticas en el caso de los
implantes. Los ataques contra un DMI pueden poner en riesgo la seguridad
del paciente que lo porta, con consecuencias fatales en ciertos casos.
Causar un mal funcionamiento intencionado en un implante puede causar
la muerte y, tal como lo reconoce la Food and Drug Administration (FDA)
de EE.UU, tales ataques deliberados podrían ser mucho más difíciles de
detectar que los ataques accidentales [61]. Además, estos dispositivos almacenan
y transmiten información médica muy delicada que requiere se
protegida, según lo dictado por las directivas europeas (por ejemplo, la Directiva 95/46/ECC) y estadunidenses (por ejemplo, la Directiva CFR
164.312) [94, 204].
Si bien todavía no se conocen incidentes reales, se han demostrado con
éxito varios ataques contra DMIs en el laboratorio [83, 133, 143]. Estos
ataques han demostrado cómo un adversario puede desactivar o reprogramar
terapias en un marcapasos con conectividad inalámbrica e incluso
inducir un estado de shock al paciente [65]. Otros ataques agotan
la batería y dejan al dispositivo inoperativo [91], lo que a menudo implica
que el paciente deba someterse a un procedimiento quirúrgico para reemplazar
la batería del DMI. Además, en el caso de los implantes cardíacos,
tienen un interruptor cuya posición de desconexión se consigue simplemente
aplicando un campo magnético intenso [149]. La existencia de este
mecanismo está motivada por la necesidad de proteger a los DMIs frete
a posibles campos electromagnéticos, por ejemplo, cuando el paciente se
somete a una cirugía cardíaca usando dispositivos de electrocauterización
[47]. Sin embargo, esto podría ser explotado fácilmente por un atacante,
ya que la activación de dicho mecanismo primitivo no requiere ningún tipo
de autenticación.
Garantizar la confidencialidad de la información almacenada y transmitida
por el DMI es otro aspecto obligatorio. El dispositivo debe implementar
políticas de seguridad apropiadas que restrinjan qué entidades
pueden reconfigurar el DMI o acceder a la información almacenada en él,
asegurando que sólo se ejecuten las operaciones autorizadas. De la misma
manera, mecanismos de seguridad deben ser implementados para proteger
el contenido de los mensajes intercambiados a través de un canal inalámbrico
no seguro.
La protección de la integridad es igualmente importante para garantizar
que la información no se haya modificado durante el tránsito. Por ejemplo,
si la información enviada por el implante al programador se altera, el
médico podría tomar una decisión equivocada. Por el contrario, si un comando
enviado al implante se falsifica, modifica o simplemente contiene
errores, su ejecución podría comprometer la integridad física del paciente.
Los mecanismos de seguridad deberían incorporarse en la fase de diseño
y complementarse con medidas legales y administrativas apropiadas.
La legislación actual es bastante permisiva a este respecto, lo que permite
el uso de implantes como marcapasos que no incorporen ningún mecanismo
de seguridad. Las autoridades reguladoras como la FDA en los Estados
Unidos o la EMA (Agencia Europea de Medicamentos) en Europa deberían
promover métricas y marcos para evaluar la seguridad de los DMIs.
Estas evaluaciones deberían ser obligatorias por ley, requiriendo un nivel
de seguridad adecuado para un implante antes de aprobar su uso. Además,
tanto las medidas de seguridad implementadas en cada DMI como los resultados
de la evaluación de su seguridad deberían hacerse públicos.
Buenas prácticas de ingeniería en los dominios de la protección y la
seguridad deberían seguirse en el diseño de los DMIs. Si se detectan errores
de hardware, a menudo esto implica un reemplazo del implante, con
los riesgos asociados y vinculados a una cirugía. Una de las principales
fuentes de fallo al tratar o monitorear a un paciente es precisamente el
mal funcionamiento del dispositivo. Estos fallos se conocen como “retiradas”,
y se estima que afectan a aproximadamente el 2,6 % de los pacientes
que llevan un implante. Además, el software que se ejecuta en el
dispositivo debe soportar estrictamente las funcionalidades requeridas para
realizar las tareas médicas y operativas para las que fue diseñado, y no más
[66, 134, 213].
En el Capítulo 1, presentamos un estado de la cuestión sobre cuestiones
de seguridad y privacidad en DMIs, discutimos los mecanismos más relevantes
propuestos para abordar estos desafíos y analizamos su idoneidad,
ventajas y principales inconvenientes. En el Capítulo 2, mostramos
cómo el uso de señales electrocardiográficas (ECGs) altamente comprimidas
(sólo 24 coeficientes de la Transformada Hadamard) es suficiente para
identificar inequívocamente individuos con un alto rendimiento (precisión
de clasificación del 97% y errores del sistema de identificación del orden
de 10−2). En el Capítulo 3 presentamos un nuevo esquema de Autenticación
Continua (AC) que, contrariamente a los trabajos previos en esta
área, considera las señales ECG como flujos de datos continuos. El sistema
propuesto de AC basado en señales cardíacas está diseñado para aplicaciones
en tiempo real y puede ofrecer una precisión de hasta el 96%,
con un rendimiento del sistema casi perfecto (estadístico kappa > 80 %).
En el Capítulo 4, proponemos un protocolo de verificación de la distancia
para gestionar el control de acceso al DMI: ACIMD. ACIMD combina
dos características, verificación de identidad (autenticación) y verificación
de la proximidad (comprobación de la distancia). El mecanismo de autenticación
es compatible con el estándar ISO/IEC 9798-2 y se realiza utilizando
la señal ECG con todas sus ondas, lo cual es difícilmente replicable
por un atacante que se encuentre distante. Hemos evaluado el rendimiento
de ACIMD usando señales ECG de 199 individuos durante 24 horas, y
hemos considerando tres estrategias posibles para el adversario. Los resultados
muestran que se puede lograr una precisión del 87.07% en la au tenticación. Finalmente, en el Capítulo 5 extraemos algunas conclusiones
y resumimos los trabajos publicados (es decir, revistas científicas con alto
factor de impacto y conferencias internacionales prestigiosas).Programa Oficial de Doctorado en Ciencia y Tecnología InformáticaPresidente: Arturo Ribagorda Garnacho.- Secretario: Jorge Blasco Alís.- Vocal: Jesús García López de Lacall
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