Systems and methods for providing a waking mechanism
An EEG monitor with sensors placed to detect signals and analyze the signals to determine if a frequency below 12 Hz, and more particularly between 3 Hz and 8 Hz, called theta waves, are present. Theta waves are generated when the brain is entering a drowsy or sleep mode. The sensors detect brain wave signals and transmit the signals to a microprocessor which analyzes the signals and determines the brain waves being detected. The brain waves are continuously monitored and the data is continuously transmitted to a microprocessor. If brain waves are detected in the predetermined range of between 3 Hz and 8 Hz the microprocessor activates a stimulus, to wake up the person wearing the device. The stimulus may be visual, auditory or tactile, such as an actuator, a phone call or any other stimulus.
1. A brain wave monitoring apparatus, comprising:
headgear configured to be secured to a head of a user;
a microprocessor coupled to the headgear;
a plurality of sensors in communication with the microprocessor and coupled to the headgear, wherein the plurality of sensors are configured to detect brain waves emitted from a brain of the user and output signals indicative of the detected brain waves; and
a stimulator coupled to the headgear;
wherein the microprocessor is configured to receive and filter the signals output from the plurality of sensors based on wave frequency to determine when to output a stimulus signal, wherein the microprocessor is configured to:
read analog signals from the sensors;
convert the analog signals to digital signals using based on an analog to digital converter;
down-sample the digital signals based on a mean value to packets;
store the packets into samples;
place the samples in a logic loop which includes a convolution with filtering coefficients assigned to the samples based on wave frequency;
normalize the samples; and
take the root mean square of the normalized samples to create data packets;
run the data packets through a packet-counter based recognition function wherein signal waves in a range of 3 Hz to 8 Hz are assigned a first filtering coefficient value and counted and signal waves in a range of greater than 8 Hz to less than 12 Hz are assigned a second filtering coefficient value and counted, wherein the first value and the second value are combined to create a packet-counter based recognition function value; and
determine when to output a stimulus signal based on a comparison of the packet-counter based recognition function value indicative of the signals to a threshold value such that when the microprocessor determines that the packet-counter based recognition function value exceeds the threshold value, the microprocessor outputs a stimulus signal to the stimulator causing the stimulator to provide a visual, auditory, or tactile stimulus to the user.
2. The apparatus of claim 1 wherein the sensors further comprise dry-contact sensors.
3. The apparatus of claim 1 , wherein the stimulator is positioned at a center base of the head when the headgear is secured to the head of the user.
4. The apparatus of claim 1 , wherein the plurality of sensors are spaced laterally across a crown of the head.
5. A brain wave monitoring apparatus, comprising
headgear configured to be secured to a head of a user;
a microprocessor coupled to the headgear;
a plurality of sensors in communication with the microprocessor and coupled to the headgear, wherein the plurality of sensors are configured to detect brain waves emitted from a brain of the user and output signals indicative of the detected brain waves; and
a stimulator coupled to the headgear;
wherein the microprocessor is configured to:
define a time interval and data size of data packets;
read signals from an analog to digital converter and place the signals in the data packets;
down-sample the signals;
store samples of the signals in the microprocessor;
pass the samples through a “for” loop that includes a convolution with filtering coefficients;
normalize the samples;
take the root mean square of the normalized samples to obtain a root mean square value;
run the root mean square value through a packet-counter based recognition function wherein signal waves from 3 Hz to 8 Hz are counted to create a first filtering coefficient value and signal waves from greater than 8 Hz to less than 12 Hz are counted to create a second filtering coefficient value, wherein the sum of the first value and the second value comprise the packet-counter based recognition function value;
compare the packet-counter based recognition function value to a threshold value; and
determine whether the packet-counter based recognition function value exceeds the threshold value, such that in response to the microprocessor determining that the packet-counter based recognition function value exceeds the threshold value, the microprocessor outputs a stimulus signal to the stimulator causing the stimulator to provide a visual, auditory, or tactile stimulus to the user.
6. The apparatus of claim 5 , wherein the signals are between 3 and 8 Hz.
7. The apparatus of claim 5 , wherein the stimulator is positioned at a center base of the head when the headgear is secured to the head of the user.
8. The apparatus of claim 5 , wherein the stimulus includes a tactile vibration.
9. The apparatus of claim 5 , wherein the stimulus includes an electric pulse.
10. The apparatus of claim 5 , wherein the plurality of sensors are spaced laterally across a crown of the head.
11. The apparatus of claim 5 , wherein the signals are indicative of the detected brain waves corresponding to the brain transitioning from an alert state to a sleep state.
12. The apparatus of claim 5 , further comprising a user-operated switch configured to reset the “for” loop.
13. A brain wave monitoring apparatus, comprising:
headgear comprising a plurality of brain wave sensors configured to detect analog brain waves;
a stimulator; and
a microprocessor configured to:
read analog signals from the sensors;
convert the analog signals to digital signals using an analog to digital converter;
down-sample the digital signals based on a mean value to packets;
store the packets into samples;
place the samples in a logic loop which includes a convolution, wherein a first filtering coefficient value is assigned to signal waves in the range of between 3 Hz to 8 Hz and a second filtering coefficient value is assigned to signal waves in the range of between 8 Hz and 12 Hz;
normalize the samples;
take the root mean square of the normalization to create data packets;
run the data packets through a packet-counter based recognition function wherein the samples having a first filtering coefficient value and the samples having a second filtering coefficient value are combined to constitute a packet-counter based recognition function value; and
determine when to output a stimulus signal based on comparison of the packet-counter based recognition function value indicative of the signals to a threshold value such that when the microprocessor determines that the packet-counter based recognition function value exceeds the threshold value the microprocessor outputs a stimulus signal to the stimulator causing the stimulator to provide a visual, auditory, or tactile stimulus to the user.