WO2019125097A1 - Method for evaluating physical fatigue and state of alertness in order to authorise the safe operation of vehicles, by measuring spontaneous pupillary oscillation signals and signals from bio-sensors - Google Patents

Method for evaluating physical fatigue and state of alertness in order to authorise the safe operation of vehicles, by measuring spontaneous pupillary oscillation signals and signals from bio-sensors Download PDF

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WO2019125097A1
WO2019125097A1 PCT/MX2017/000154 MX2017000154W WO2019125097A1 WO 2019125097 A1 WO2019125097 A1 WO 2019125097A1 MX 2017000154 W MX2017000154 W MX 2017000154W WO 2019125097 A1 WO2019125097 A1 WO 2019125097A1
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alertness
pupillary
pupil
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specified
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Dino Alejandro PARDO GUZMÁN
Antonio MARÍN HERNÁNDEZ
Marcos Antonio SÁNCHEZ GONZÁLEZ
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Pardo Guzman Dino Alejandro
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  • the present invention has its predominant field of application in methods for evaluation of physical fatigue and alertness, specifically to authorize the safe operation of heavy vehicles based on their physical / mental state by means of measurements of Spontaneous Pupil Oscillation signals and bio-signals .
  • Patent US20160256049A1 discloses a method of analyzing bodily reactions to external stimuli with the use of a microprocessor diagnostic system is characterized in that the image obtained from the camera is analyzed in a microprocessor system, in which the image is obtained by exposure of the eye to visible light emitted by an illuminator, and then a video sequence is recorded, and the analysis is performed by the microprocessor executing a program that implements an image analysis algorithm for the detection of characteristics of the image that allow its identification, and first the eye is detected, and then, in the region of its pupil, the geometrical parameters of the pupil are ruled out and its changes over time, and on the basis of the data obtained a diagnostic module generates a test result transmitted to a database.
  • a method of screening a pupil of a subject is described to determine if the pupillary reflex resembles a canonical pupillary reflex.
  • the method comprises the steps of stimulating the pupil with a stimulus source, such as a pupilometer and determining if any of the various pupillary response conditions are met.
  • Patent US20150045012A1 discloses a pupilometry system comprising: a mobile telephone cover comprising a housing capable of receiving a mobile telephone, in which the design comprises a telecentric lens, one or more IR LEDs, one or more visible LEDs , and means for communicating digital information or commands between the mobile phone cover and the mobile telephone.
  • a system and a method include a training framework implemented by computer that adapts its behavior to different types of training objectives.
  • the system uses a measured neurophysiological state of a student to provide at least one self-regulatory feedback and training environment feedback to optimize a learning experience for one or more different types of scenarios.
  • the claim system in which the received bio-signals correspond to bio-signals generated by multiple sensors selected from the group consisting of an electroencephalograph, an electrocardiograph, a galvanic skin response sensor, a heart rate variability sensor and a pupilometric sensor.
  • US20160192837 A1 pupilometry systems for measuring one or more pupillary characteristics of a patient are shown and described.
  • Puillometric systems include at least one camera for capturing image data from one or snooping pupils, at least one radiation source configured to project radiation to one or more pupils, and a computer system in communication of data with the at least one camera, the computer having a processor and a non-transient storage medium readable by computer.
  • Patent US20140313488A1 presents a method for measuring and analyzing an ocular response in a subject comprising the steps of: providing a system based on video oculography for the subject, with the system configured to collect eye images in excess of 60 hz and configured to resolve minor eye movements of at least 3 degrees of movement; Collecting ocular data with the system based on video oculography in which at least one stimulus is presented to only one eye of the subject and is configured to oroduce a pupil eye response from at least one eye of the subject; Calculation of pupilometry measurements from the eye data, in which the pupil measurements are calculated independently for the left and right eyes of the subject for each stimulus presented to the subject, and where the comparative measurements of left and right pupilometry are calculated of the eye data; analyze the ocular response of a subject based on at least one of the calculated pupilometry measurements.
  • the pupilometer may comprise an imaging sensor for generating signals representative of a pupil of an eye, a data processor; and a program executable by the data processor to allow the data processor to process signals received from the imaging sensor and thereby identify one or more regions of non-uniformity within an image of a perimeter of the pupil.
  • Figure 1 is a schematic diagram of the steps of the method of the present invention.
  • FIG. 2 is a schematic diagram of the detection of the diameter of the pupil [201].
  • an image pre-processing algorithm [103] is applied to segment, detect, and model time-frequency patterns of Spontaneous Pupil Oscillation signals by applying the Hilbert-Huang (HHT) transform and where the pre-processing includes the detection and elimination of blinking and interpolation of images followed by the application of the empirical Modal Decomposition Method (EMD) to describe the behavior of the OPE as the superposition of Intrinsic Modal Functions (MFIs).
  • EMD empirical Modal Decomposition Method
  • an algorithm [103] is applied to calculate general parameters a) Basal diameter (self-referenced parameter to pupil diameter without stimuli); b) Constraint speed at the end of dilation, c) Minimum opening after stimulation, d) Reflex amplitude (amplitude of the pupillary reflex to light, e) Percentage of reflex amplitude of the initial diameter, f) Dilation time 75 percent of the reflected amplitude, g) index of pupil restlessness, and h) Cumulative pupil variability rate.
  • the clinical history [105] is analyzed with current diseases and types of medications used, and the physical state of the driver by means of the multidimensional module [106] that contains sensors to measure heart rate, blood oxygen level and temperature.
  • IIP pupillary anxiety index

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Abstract

The invention relates to a method for evaluating physical fatigue and state of alertness in order to authorise the safe operation of vehicles, based on physical/mental state, by measuring spontaneous pupillary oscillation signals and signals from bio-sensors.

Description

MÉTODO PARA EVALUACIÓN DE CANSANCIO FÍSICO Y ESTADO DE ALERTA PARA AUTORIZAR LA OPERACIÓN SEGURA DE VEHÍCULOS MEDIANTE MEDICIONES DE SEÑALES DE OSCILACIÓN PUPILAR ESPONTANEA Y BIO-SENSORES  METHOD FOR EVALUATION OF PHYSICAL TIREDNESS AND STATE OF ALERT TO AUTHORIZE THE SAFE OPERATION OF VEHICLES BY MEASUREMENTS OF SPONTANEOUS PUPILAR AND BIO-SENSOR OSCILLATION SIGNALS
CAMPO TÉCNICO DE LA INVENCIÓN TECHNICAL FIELD OF THE INVENTION
La presente invención tiene su campo de aplicación preponderante en métodos para evaluación de cansancio físico y estado de alerta, específicamente para autorizar la operación segura de vehículos pesados en base a su estado físico/mental mediante mediciones de señales de Oscilación Pupilar Espontanea y bio-señales.  The present invention has its predominant field of application in methods for evaluation of physical fatigue and alertness, specifically to authorize the safe operation of heavy vehicles based on their physical / mental state by means of measurements of Spontaneous Pupil Oscillation signals and bio-signals .
ANTECEDENTES DE LA INVENCIÓN BACKGROUND OF THE INVENTION
Los largos horarios en las empresas mineras, generalmente de 12 horas diarias, provocan un cansancio en los trabajadores. Además, se encuentran estudios donde, el 25% de los operadores de camiones utilizan medicamentos de categoría II y III, categorías impuestas por DRUID. De este porcentaje hay tres fallos humanos que suman el 60% de este tipo de accidentalidad: Alcohol, velocidad y distracciones. De estos tres fallos, dos de ellos pueden prevenirse o evitar (Velocidad y Distracción) el otro no (alcohol). Existen tres tipos de distracción durante la conducción (Visual, manual y cognitiva o mental), de las cuales la visual y la manual son las dos distracciones que se pueden detectar con mucha precisión ya que estas distracciones implican el movimiento de cabeza o mirada de conductor, por otro lado la distracción cognitiva o mental es imprecisa ya que implica que el conductor mira hacia el horizonte de la carretera sin enfocar lo que significa que la mente del conductor no se centra en la conducción, esto es provocado por problemas personales o por soñar despierto. The long hours in the mining companies, usually 12 hours a day, cause a fatigue in the workers. In addition, there are studies where, 25% of truck operators use drugs of category II and III, categories imposed by DRUID. Of this percentage there are three human failures that add up to 60% of this type of accident: Alcohol, speed and distractions. Of these three failures, two of them can be prevented or avoided (Speed and Distraction) the other does not (alcohol). There are three types of distraction during driving (Visual, manual and cognitive or mental), of which the visual and the manual are the two distractions that can be detected with great precision since these distractions involve head movement or driver's eyes. , on the other hand the cognitive or mental distraction is imprecise since it implies that the driver looks towards the horizon of the road without focusing what means that the mind of the driver is not focused on driving, this is caused by personal problems or by dreaming awake.
A continuación, se presenta una revisión en propiedad intelectual: Next, a review on intellectual property is presented:
En la patente US20160256049A1 se describe un método de análisis de reacciones corporales a estímulos externos con el uso de un sistema de diagnóstico por microprocesador se caracteriza porque la imagen obtenida de la cámara es analizada en un sistema de microprocesador, en el que la imagen se obtiene por exposición del ojo a luz visible emitida por un iluminador, y luego se registra una secuencia de vídeo, y el análisis es realizado por el microprocesador ejecutando un programa que implementa un algoritmo de análisis de imagen para la detección de características de la imagen que permiten su identificación , y en primer lugar se detecta el ojo, y luego, en la región de su pupila, se rüden los parámetros geométricos de la pupila y sus cambios en el tiempo, y sobre la base de los datos obtenido un módulo de diagnóstico genera un resultado de prueba transmitido a una base de datos. Patent US20160256049A1 discloses a method of analyzing bodily reactions to external stimuli with the use of a microprocessor diagnostic system is characterized in that the image obtained from the camera is analyzed in a microprocessor system, in which the image is obtained by exposure of the eye to visible light emitted by an illuminator, and then a video sequence is recorded, and the analysis is performed by the microprocessor executing a program that implements an image analysis algorithm for the detection of characteristics of the image that allow its identification, and first the eye is detected, and then, in the region of its pupil, the geometrical parameters of the pupil are ruled out and its changes over time, and on the basis of the data obtained a diagnostic module generates a test result transmitted to a database.
En la patente US20150297074A1 Se describe un método de cribado de una pupila de un sujeto para determinar si el reflejo pupilar se parece a un refleje pupilar canónico. El método comprende las etapas de estimular la pupila con un-j fuente de estímulo, tal como un pupilómetro y determinar si se cumple alguna de las diversas condiciones de respuesta pupilar. In the patent US20150297074 A1 a method of screening a pupil of a subject is described to determine if the pupillary reflex resembles a canonical pupillary reflex. The method comprises the steps of stimulating the pupil with a stimulus source, such as a pupilometer and determining if any of the various pupillary response conditions are met.
En la patente US20150045012A1 se describe un sistema de pupilometría que comprende: una cubierta de teléfono móvil que comprende un alojamiento capaz de recibir un teléfono móvil, en el que el diseño comprende una lente telecéntríca, uno o más LED IR, uno o más LEDs visibles, y medios para comunicar información digital o comandos entre la cubierta del teléfono móvil y el teléfono móvil.  Patent US20150045012A1 discloses a pupilometry system comprising: a mobile telephone cover comprising a housing capable of receiving a mobile telephone, in which the design comprises a telecentric lens, one or more IR LEDs, one or more visible LEDs , and means for communicating digital information or commands between the mobile phone cover and the mobile telephone.
En la patente US8620419 B2 se presenta un sistema y un método incluyen un marco de formación implementado por ordenador que adapta su comportamiento a diferentes tipos de objetivos de formación. El sistema utiliza un estado neurofisiológico medido de un estudiante para proporcionar al menos uno de retroalimentación de autorregulación y feedback de ambiente de entrenamiento para optimizar una experiencia de aprendizaje para uno o más tipos diferentes de escenarios. El sistema de reivindicación en el que los bio-señales recibidas corresponden a bio-señales generados por múltiples sensores seleccionados del grupo que consiste en un electroencefalógrafo, un electrocardiógrafo, un sensor galvánico de respuesta cutánea, un sensor de variabilidad de la frecuencia cardíaca y un sensor pupilométrico. En la patente US20160192837 A1 se muestran y describen unos sistemas de pupilometría para medir una o más características pupilares de un paciente. Los sistemas puillométricos incluyen al menos una cámara para capturar datos de imagen de una o pupilas de ronquido, al menos una fuente de radiación configurada para proyectar radiación a uno o más pupilas, y un sistema informático en comunicación de datos con la al menos una cámara, el ordenador que tiene un procesador y un medio de almacenamiento no transitorio legible por ordenador. In the patent US8620419 B2 a system and a method are presented include a training framework implemented by computer that adapts its behavior to different types of training objectives. The system uses a measured neurophysiological state of a student to provide at least one self-regulatory feedback and training environment feedback to optimize a learning experience for one or more different types of scenarios. The claim system in which the received bio-signals correspond to bio-signals generated by multiple sensors selected from the group consisting of an electroencephalograph, an electrocardiograph, a galvanic skin response sensor, a heart rate variability sensor and a pupilometric sensor. In US20160192837 A1, pupilometry systems for measuring one or more pupillary characteristics of a patient are shown and described. Puillometric systems include at least one camera for capturing image data from one or snooping pupils, at least one radiation source configured to project radiation to one or more pupils, and a computer system in communication of data with the at least one camera, the computer having a processor and a non-transient storage medium readable by computer.
En la patente US20140313488A1 se presenta un método para medir y analizar una respuesta ocular en un sujeto que comprende las etapas de: proporcionar un sistema basado en oculografía de vídeo para el sujeto, con el sistema configurado para recoger imágenes de ojo en exceso de 60 hz y configurado para resolver movimientos oculares menores de al menos 3 grados de movimiento; Recoger datos oculares con el sistema basado en oculografía de vídeo en el que si menos un estímulo se presenta a sólo un ojo del sujeto y está configurado para oroducir una respuesta ocular pupilar de al menos un ojo del sujeto; Cálculo de mediciones de pupilometría a partir de los datos de ojo, en el que las mediciones de pupila se calculan independientemente para los ojos izquierdo y derecho del sujeto para cada estímulo presentado al sujeto, y donde se calculan las medidas comparativas de pupilometría izquierda y derecha de los datos de ojo; analizar la respuesta ocular de un sujeto basándose en al menos una de las mediciones de pupilometría calculadas. Patent US20140313488A1 presents a method for measuring and analyzing an ocular response in a subject comprising the steps of: providing a system based on video oculography for the subject, with the system configured to collect eye images in excess of 60 hz and configured to resolve minor eye movements of at least 3 degrees of movement; Collecting ocular data with the system based on video oculography in which at least one stimulus is presented to only one eye of the subject and is configured to oroduce a pupil eye response from at least one eye of the subject; Calculation of pupilometry measurements from the eye data, in which the pupil measurements are calculated independently for the left and right eyes of the subject for each stimulus presented to the subject, and where the comparative measurements of left and right pupilometry are calculated of the eye data; analyze the ocular response of a subject based on at least one of the calculated pupilometry measurements.
En la patente US6116736A presenta un pupilómetro que tiene capacidad de detección de una irregularidad de pupila o de no uniformidad. El pupilómetra puede comprender un sensor de formación de imágenes para generar señales representativas de una pupila de un ojo, un procesador de datos; y un programa ejecutable por el procesador de datos para permitir que el procesador de datos procese señales recibidas del sensor de formación de imágenes e identificar de ese modo una o más regiones de no uniformidad dentro de una imagen de un perímetro de la pupila. In the patent US6116736A presents a pupilometer that has ability to detect a pupil irregularity or non-uniformity. The pupilometer may comprise an imaging sensor for generating signals representative of a pupil of an eye, a data processor; and a program executable by the data processor to allow the data processor to process signals received from the imaging sensor and thereby identify one or more regions of non-uniformity within an image of a perimeter of the pupil.
DESCRIPCION DETALLADA DE LA INVENCIÓN DETAILED DESCRIPTION OF THE INVENTION
Los detalles característicos de la presente invención, se muestran claramente en la siguiente descripción y en las figuras que se acompañan, las cuales se mencionan a manera de ejemplo, por lo que no deben considerarse como una limitante para dicha invención. The characteristic details of the present invention are clearly shown in the following description and in the accompanying figures, which are mentioned by way of example, so they should not be considered as a limitation for said invention.
Breve descripción de las figuras: Brief description of the figures:
La figura 1 es un diagrama esquemático de las etapas del método, de la presente invención. Figure 1 is a schematic diagram of the steps of the method of the present invention.
La figura 2 es diagrama esquemático de la detección del diámetro de la pupila [201 ]. A continuación, se describe uno de los métodos donde se puede utilizar el presente sistema, empieza con la entrada [101] de datos por el módulo de visión artificial [102] con sistema opto mecánico para control de haz luminoso led y sensado VISIR para capturar imágenes de alto contraste Pupila-Iris, se aplica un algoritmo de pre-procesamiento de imágenes [103] para segmentar, detectar, y modelar patrones en tiempo-frecuencia de las señales de Oscilación Pupilar Espontanea aplicando la transformada Hilbert-Huang (HHT) y donde el pre-procesamiento incluye la detección y eliminación del parpadeo e interpolación de imágenes seguido de la aplicación del Método de Descomposición Modal empírica (EMD) para describir el comportamiento de la OPE como la superposición de Funciones Modales Intrínsecas (IMFs). A continuación se aplica un algoritmo [103] para cálculo de parámetros generales a) Diámetro basal (parámetro auto referenciado ai diámetro pupilar sin estímulos); b) Velocidad de constricción al final de la dilatación, c) Apertura mínima luego de la estimulación, d) Amplitud refleja (amplitud del reflejo pupilar a la luz, e) Porcentaje de amplitud refleja del diámetro inicial, f) Tiempo de dilatación 75 por ciento de la amplitud refleja, g) índice de inquietud pupilar, y h) Tasa de variabilidad pupilar acumulada.  Figure 2 is a schematic diagram of the detection of the diameter of the pupil [201]. Next, one of the methods where the present system can be used is described, starting with the input [101] of data by the artificial vision module [102] with opto mechanical system for LED beam control and VISIR sensing to capture high-contrast Pupil-Iris images, an image pre-processing algorithm [103] is applied to segment, detect, and model time-frequency patterns of Spontaneous Pupil Oscillation signals by applying the Hilbert-Huang (HHT) transform and where the pre-processing includes the detection and elimination of blinking and interpolation of images followed by the application of the empirical Modal Decomposition Method (EMD) to describe the behavior of the OPE as the superposition of Intrinsic Modal Functions (MFIs). Next, an algorithm [103] is applied to calculate general parameters a) Basal diameter (self-referenced parameter to pupil diameter without stimuli); b) Constraint speed at the end of dilation, c) Minimum opening after stimulation, d) Reflex amplitude (amplitude of the pupillary reflex to light, e) Percentage of reflex amplitude of the initial diameter, f) Dilation time 75 percent of the reflected amplitude, g) index of pupil restlessness, and h) Cumulative pupil variability rate.
Así mismo se analizan [ 04] el historial clínico [105] con enfermedades actuales y tipos de medicamentos utilizados, y estado físico del conductor por medio del módulo multidimensional [106] que contiene sensores para medir ritmo cardíaco, nivel de oxígeno en la sangre y temperatura.  Likewise, [04] the clinical history [105] is analyzed with current diseases and types of medications used, and the physical state of the driver by means of the multidimensional module [106] that contains sensors to measure heart rate, blood oxygen level and temperature.
Un algoritmo de para toma de decisión [107] y determinación de trastornos del sueño y nivel de alerta [108], determina el índice de inquietud pupilar (IIP) mediante identificación y análisis de las llamadas "ondas de somnolencia", si su IIP es normal se autoriza la conducción de la unidad y termina la evaluación [109], si no, descarta al conductor al menos hasta que recupere su estado de alerta. An algorithm for decision making [107] and determination of sleep disorders and alert level [108], determines the pupillary anxiety index (IIP) by identifying and analyzing the so-called "drowsiness waves", if your PII is normal the driving of the unit is authorized and the evaluation is completed [109], if not, discard the driver at least until he regains his alertness.

Claims

REIVINDICACIONES
1. La presente invención describe un método para evaluación de cansancio físico y estado de alerta para autorizar la operación segura de vehículos en base a su estado físico/mental mediante mediciones de señales de Oscilación Pupilar Espontanea y bio-sensores, comprendido por los siguientes elementos:  1. The present invention describes a method for assessing physical fatigue and alertness to authorize the safe operation of vehicles based on their physical / mental state by means of measurements of Spontaneous Pupil Oscillation signals and bio-sensors, comprised of the following elements :
a. Recolección de base de datos del historial clínico de conductores. to. Collection of database of the clinical history of drivers.
b. Una unidad de procesamiento para analizar datos generados por d; erentes módulos y sensores. b. A processing unit to analyze data generated by d ; Different modules and sensors.
c. Un módulo de visión artificial con sistema opto mecánico para control de haz luminoso led y sensado VIS-IR para captura de Imágenes de alto contraste Pupila-Iris. c. An artificial vision module with opto mechanical system for LED light beam control and VIS-IR sensing for high-contrast Pupil-Iris images.
d. Un algoritmo de pre-procesamiento de imágenes para segmentar, detectar, y modelar patrones en tiempo-frecuencia de las señales de Oscilación Pupilar Espontanea aplicando la transformada Hilbert-Huang (HHT). d. An image pre-processing algorithm to segment, detect, and model time-frequency patterns of Spontaneous Pupil Oscillation signals by applying the Hilbert-Huang transform (HHT).
e. Un algoritmo para cálculo de parámetros generales a) Diámetro basal (parámetro auto referenciado al diámetro pupilar sin estímulos); b) Velocidad de constricción al final de la dilatación, c) Apertura mínima luego de la estimulación, d) Amplitud refleja (amplitud del reflejo pupilar a la luz, e) Porcentaje de amplitud refleja del diámetro inicial, f) Tiempo de dilatación 75 por ciento de la amplitud refleja, g) índice de inquietud pupilar, y h) Tasa de variabilidad pupilar acumulada. and. An algorithm for calculating general parameters a) Basal diameter (self-referenced parameter to pupillary diameter without stimuli); b) Constraint speed at the end of dilation, c) Minimum opening after stimulation, d) Reflex amplitude (amplitude of the pupillary reflex to light, e) Percentage of reflex amplitude of the initial diameter, f) Dilation time 75 percent of the reflected amplitude, g) index of pupil restlessness, and h) Cumulative pupil variability rate.
f. Un algoritmo de para toma de decisión y determinación de trastornos del sueño y nivel de alerta, determinando el índice de inquietud pupilar (IIP) mediante identificación y análisis de las llamadas "ondas de somnolencia", definidas por oscilaciones pupilares espontáneas de baja frecuencia, gran amplitud, disminución progresiva del diámetro pupilar y por análisis de señales de biosensores. F. An algorithm for decision making and determination of sleep disorders and alertness level, determining the index of pupillary restlessness (PII) by identifying and analyzing the so-called "sleepiness waves", defined by spontaneous low-frequency pupillary oscillations. amplitude, progressive diminution of the pupillary diameter and by analysis of signals of biosensors.
g. Modulo multidimensional para evaluación de cansancio físico y estado de alerta para autorizar la operación segura de vehículos, considerando parámetros auto- referenciados. g. Multidimensional module for evaluation of physical fatigue and alertness to authorize the safe operation of vehicles, considering self-referenced parameters.
2. Un método como el especificado en Reivindicación 1 , donde el historial clínico incluye a) enfermedades actuales, b) enfermedades padecidas en el pasado y c) uso y tipo de medicamentos utilizados. 2. A method as specified in Claim 1, where the clinical history includes a) current diseases, b) diseases suffered in the past and c) use and type of drugs used.
3. Un método como el especificado en Reivindicación 1 , donde el pre- procesamiento incluye la detección y eliminación del parpadeo e interpolación de imágenes seguido de la aplicación del Método de Descomposición Modal empírica (EMD) para describir el comportamiento de la SPO como la superposición de Funciones Modales Intrínsecas (IMFs). 3. A method as specified in Claim 1, wherein the pre-processing includes the detection and elimination of blinking and interpolation of images followed by the application of the Empirical Modal Decomposition Method (EMD) to describe the behavior of the SPO as the superposition of Intrinsic Modal Functions (MFIs).
4. Un método como el especificado en Reivindicación 3, donde las fundones modales intrínsecas son mutuamente ortogonales y contiene solo una componente frecuencial que pueden ser separadas factiblemente en sus componentes de AM y FM.  4. A method as specified in Claim 3, where the intrinsic modal modes are mutually orthogonal and contain only one frequency component that can be feasibly separated into their AM and FM components.
5. Un método como el especificado en Reivindicación 4, donde las funciones de modo intrínseco IMF, son relacionadas con la somnolencia, estado de alerta y consumo de alcohol, drogas o medicamentos con efecto en la conducción de vehículos. 5. A method as specified in Claim 4, where the intrinsic MFI functions are related to drowsiness, alertness and consumption of alcohol, drugs or drugs with effect on the driving of vehicles.
6. Un método como el especificado en Reivindicación 1, donde el algoritmo de estudio de trastornos del sueño y nivel de alerta es para determinar e estado de alerta en individuos que a) padecen diabetes mellitas, parkinson, migraña, o síndrome de fatiga crónica, b) consumen medicamentos categoría I, II o III en escala DRUID, y/o c) están bajo los efectos del alcohol (dimensionado con ayuda de etilómetro) u opioides.  6. A method as specified in Claim 1, wherein the algorithm for studying sleep disorders and alert level is to determine alertness in individuals who a) have diabetes mellitus, parkinson's, migraine, or chronic fatigue syndrome, b) consume drugs category I, II or III in DRUID scale, and / or c) are under the influence of alcohol (measured with the help of an ethylmeter) or opioids.
7. Un método como el especificado en Reivindicación 1 , donde el modulo multidimensional para evaluación de cansancio físico y estado de alerta contiene sensores para medir ritmo cardíaco, nivel de oxígeno en la sangre y temperatura. 7. A method as specified in Claim 1, wherein the multidimensional module for evaluation of physical fatigue and alertness contains sensors for measuring heart rate, blood oxygen level and temperature.
PCT/MX2017/000154 2017-12-19 2017-12-19 Method for evaluating physical fatigue and state of alertness in order to authorise the safe operation of vehicles, by measuring spontaneous pupillary oscillation signals and signals from bio-sensors WO2019125097A1 (en)

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