Portable stand for pathway illumination

1 . A portable stand comprising:

a rotating platform housing an electronic device;

a wheel operatively connected to the rotating platform; and

an auto-balancing system to maintain proper orientation of the rotating platform during movement,

wherein the electronic device comprises:

a processor that trains a machine learning algorithm by:

collecting sensor data representing user movement patterns and user task completion patterns during initial device use;

establishing baseline task completion patterns specific to baseline cognitive capabilities of a user and the sensor data;

implementing pattern recognition algorithms to identify deviations from baseline performance; and

establishing updated task completion patterns to align with a predefined sequence of daily activities of the user;

a camera mounted on the rotating platform to scan an environment;

a sensor operatively connected to the processor to sense the environment and a user positioned in the environment;

a projector operatively connected to the processor, wherein the projector comprises a laser emitter to produce visible light, and a waveguide to optically direct illuminated pathways containing the visible light in a plurality of angles through optical redirection in the environment;

a display screen operatively connected to the processor; and

a memory storing instructions executable by the processor,

wherein the processor controls alignment of the camera, projector, and sensor based on stand movement, and

wherein the processor processes raw sensor data from the sensor through a signal conditioning algorithm that filters noise and normalizes variations in sensor response before analysis by the machine learning algorithm,

wherein the machine learning algorithm establishes personalized timing thresholds based on a user performance history,

wherein the processor modifies outputs of linked hardware devices when the user does not move toward an illuminated pathway within an established timing threshold by increasing an illumination intensity of the projector, and activating an output displayed on the display screen, or a combination thereof,

wherein the processor is configured to generate periodic cognitive assessment reports based on task performance data, and

wherein the processor is configured to alert caregivers if the user task completion patterns indicate declining cognitive function of the user based on comparisons to learning patterns of the machine learning algorithm.

2 . The portable stand of claim 1 , wherein the stand is height-adjustable.

3 . The portable stand of claim 1 , comprising a portable battery pack to supply power to the electronic device.

4 . The portable stand of claim 1 , comprising a motor operatively connected to the wheel.

5 . The portable stand of claim 1 , wherein the electronic device comprises a smartphone or tablet device.

6 . The portable stand of claim 1 , wherein the projector contains auto-focus capabilities to ensure properly aligned pathway projection even when the stand is in motion.

7 . The portable stand of claim 1 , wherein the processor continuously calibrates the camera, projector, and sensor based on stand movement.

8 . A portable stand for cognitive guidance assistance, the stand comprising:

a rotatable platform;

a wheel operatively connected to the rotatable platform;

an electronic device operatively connected to the rotatable platform, wherein the electronic device comprises:

a camera operatively connected to a processor;

a sensor operatively connected to the processor;

a projector operatively connected to the processor;

a display screen operatively connected to the processor; and

a speaker operatively connected to the processor, and

wherein the processor is configured to:

train a machine learning algorithm by:

collecting sensor data representing user movement patterns and environmental interactions during initial device use;

establishing baseline task completion patterns specific to baseline cognitive capabilities of a user and the sensor data;

implementing pattern recognition algorithms to identify deviations from baseline performance; and

establishing updated task completion patterns to align with a predefined sequence of daily activities for the user;

instruct the projector to project a first illuminated pathway between a current location of a user and a first target location based on the predefined sequence of daily activities for the user and the updated task completion patterns established by the machine learning algorithm;

present at least one of task-specific audio and visual instructional content through at least one of the display screen and speaker for a current activity in the predefined sequence of daily activities analyzed by the machine learning algorithm;

analyze activity data captured by the camera and the sensor to monitor completion of the current activity;

deactivate projection of the first illuminated pathway from the projector upon detecting user arrival at the first target location; and

control an operational output of the projector to adjust pathway routing, intensity, and illumination characteristics, or a combination thereof, of illuminated pathways, based on the updated task completion patterns established by the machine learning algorithm,

wherein the projector comprises (i) a laser emitter to produce visible light, and (ii) a waveguide to optically direct the illuminated pathway in a plurality of angles through optical redirection, and

wherein the processor processes raw sensor data from the sensor through a signal conditioning algorithm that filters noise and normalizes variations in sensor response before analysis by the machine learning algorithm,

wherein the machine learning algorithm establishes personalized timing thresholds based on a user performance history,

wherein the processor modifies outputs of linked hardware devices when the user does not move toward the first illuminated pathway within an established timing threshold by increasing an illumination intensity of the projector, and activating an output displayed on the display screen, or a combination thereof,

wherein the processor is configured to generate periodic cognitive assessment reports based on task performance data, and

wherein the processor is configured to alert caregivers if the task completion patterns indicate declining cognitive function of the user based on comparisons to learning patterns of the machine learning algorithm.

9 . The portable stand of claim 8 , comprising a gyroscope to maintain proper orientation of the stand.

10 . The portable stand of claim 8 , comprising a rotating platform on which the camera and sensor are mounted.

11 . The portable stand of claim 8 , wherein the projector contains auto-focus capabilities to ensure properly aligned pathway projection even when the stand is in motion.

12 . The portable stand of claim 8 , wherein the laser emitter is calibrated to produce visible light within wavelength ranges of approximately 500-550 nm and 570-590 nm.

13 . The portable stand of claim 8 , wherein the sensor comprises at least one environmental sensor and at least one motion sensor.

14 . The portable stand of claim 8 , wherein the processor is configured to ensure consistent guidance functionality whether the stand is stationary or being relocated within the environment.

15 . A non-transitory computer-readable medium storing instructions that, when executed by a processor of a portable guidance device mounted on a portable stand with a wheel, cause the processor to:

train a machine learning algorithm by:

collecting sensor data representing user movement patterns and environmental interactions during initial device use;

establishing baseline task completion patterns specific to baseline cognitive capabilities of a user and the sensor data;

implementing pattern recognition algorithms to identify deviations from baseline performance; and

establishing updated task completion patterns to align with a predefined sequence of daily activities for the user;

control a projector comprising a laser emitter and a waveguide to project visible light beams through the waveguide to create illuminated pathways in a plurality of angles;

process raw sensor data from at least one sensor through signal conditioning algorithms that filter noise and normalize variations in sensor response;

analyze the processed sensor data using the machine learning algorithm;

identify a current location of a user based on data captured by a camera;

instruct the projector to project a first illuminated pathway between the current location and a first target location based on the predefined sequence of daily activities for the user and the updated task completion patterns established by the machine learning algorithm;

present task-specific instructional content through at least one of a display screen and a speaker;

analyze activity data captured by the camera and the at least one sensor to monitor completion of a current activity;

deactivate projection of the first illuminated pathway upon detecting user arrival at the first target location;

instruct the projector to project a second illuminated pathway from the first target location to a second target location upon verification of completion of the current activity;

control an operational output of the projector to adjust pathway routing, intensity, and illumination characteristics, or a combination thereof, of the illuminated pathways, based on the updated task completion patterns established by the machine learning algorithm;

establish personalized timing thresholds based on a user performance history;

modify outputs of linked hardware devices when the user does not move toward the first illuminated pathway within an established timing threshold by increasing an illumination intensity of the projector, and activating an output displayed on the display screen, or a combination thereof;

generate periodic cognitive assessment reports based on task performance data; and

alert caregivers if the task completion patterns indicate declining cognitive function of the user based on comparisons to learning patterns of the machine learning algorithm.

16 . The non-transitory computer-readable medium of claim 15 , wherein the instructions further cause the processor to:

access a predetermined daily routine schedule of the user; and

initiate activation of the illuminated pathways at predetermined times according to the daily routine schedule.

17 . The non-transitory computer-readable medium of claim 15 , wherein the machine learning algorithm implements specialized pattern recognition techniques trained on datasets of confusion indicators to detect when user confusion occurs during task performance.

18 . The non-transitory computer-readable medium of claim 15 , wherein the machine learning algorithm utilizes supervised learning methods with labeled examples of normal and atypical performance, unsupervised learning that identifies natural clusters in performance data, or reinforcement learning that progressively refines detection accuracy through continuous performance feedback.

19 . The portable stand of claim 1 , wherein the processor is configured to:

continuously update a three-dimensional model of the environment based on data from the sensor;

detect and classify environmental conditions that could obstruct the illuminated pathways;

dynamically recalculate the illuminated pathways based on detected obstacles; and

maintain a database of frequently used items of the user and their last known locations in the environment.

20 . The portable stand of claim 1 , wherein the processor is configured to:

monitor ambient conditions in the environment affecting completion of a current activity;

adjust lighting levels of the illuminated pathways based on time of day and activity requirements;

detect environmental hazards in the environment using the sensor; and

integrate with a smart home system for automated environmental control.