Procedures for assessing a driver's health

Abstract

The invention relates to a method for assessing the health of a driver of a motor vehicle, wherein driver behavior (FV) is described by health factors (GF) of the driver, which are determined by sensors (S) arranged in the motor vehicle and / or in a smartphone and / or sports armband, wherein the health factors (GF) are evaluated and weighted in order to determine at least one Fit Score (FS) as a measure of the driver's health and output it on at least one human-machine interface in the motor vehicle and / or on the smartphone and / or on the sports armband, wherein behavioral recommendations (VE) to improve the Fit Score (FS) are generated and output on the human-machine interface, wherein a gamification approach to increase the Fit Score (FS) is applied, and wherein a time course of the Fit Score (FS) is output on the human-machine interface.

Description

[0001] The invention relates to a method for assessing the health of a driver according to the preamble of claim 1.

[0002] According to the Techniker Krankenkasse health report, the occupational group "drivers of vehicles and transport equipment" has the highest number of sick days, as excessive sitting has a variety of negative effects on health and attention. In 2021, members of this occupational group were unable to work for an average of 25.2 days, resulting in high costs for their employers.

[0003] WO 2016 / 070981 A1 describes a system and a method for monitoring the health status of a vehicle occupant. The system comprises a control unit which includes: a receiver for wirelessly receiving physiological parameters from at least one body-worn unit which includes one or more sensors for determining one or more physiological parameters of the vehicle occupant, and a diagnostic module designed to derive information about the health status, well-being, or cases of illness, at least partially, based on the received physiological parameters.The control unit is also designed to provide the vehicle occupant with information about their health status via at least one output unit of the vehicle and to initiate at least one of the following steps: adapting the vehicle functions to the condition, or suggesting or interactively carrying out condition-improving measures via at least one output unit of the vehicle.

[0004] The invention is based on the objective of providing a novel method for assessing the health of a driver.

[0005] The problem is solved according to the invention by a method for assessing the health of a driver with the features of claim 1.

[0006] Advantageous embodiments of the invention are the subject of the dependent claims.

[0007] A method for assessing the health of a motor vehicle driver is proposed, wherein driver behavior is described by health factors of the driver, which are determined by sensors arranged in the motor vehicle and / or in a smartphone and / or fitness tracker. The health factors are evaluated and weighted to determine at least one Fit Score as a measure of the driver's health and are displayed on at least one human-machine interface in the motor vehicle and / or on the smartphone and / or on the fitness tracker. Behavioral recommendations for improving the Fit Score are generated and displayed on the human-machine interface. According to the invention, a gamification approach is used to increase the Fit Score, with a time-based progression of the Fit Score being displayed on the human-machine interface.

[0008] The solution according to the invention can improve the health of members of the occupational group "drivers of vehicles and transport equipment" by providing playful and visually presented information about their health status. The motivation for healthier behavior among the occupants is to be increased through the use of the Fit Score in the vehicle. A gamification approach provides additional motivation and recommendations for members of this occupational group.

[0009] Exemplary embodiments of the invention are explained in more detail below with reference to a drawing.

[0010] This shows: Fig. 1. A schematic view of a system and procedure for assessing the health of a motor vehicle driver

[0011] The only Fig.Figure 1 is a schematic view of a system and procedure for assessing the health of a motorist, which makes suggestions on how it can be improved.

[0012] The process uses as input I a driver behavior FV, described by health factors GF, which are recorded by sensors S. The process generates two outputs O: a fit score FS and behavioral recommendations VE. This output O, for example through gamification incentives, influences the input I, potentially leading to an improvement in driver behavior FV and thus an improvement in driver health.

[0013] The various sensors (S) record data, which is then sent to a server. There, the data is processed, and the health factors (GF) are calculated, analyzed, and at least one Fit Score (FS) is determined. Based on the Fit Score (FS), behavioral recommendations (VE) are generated. These behavioral recommendations (VE) and the Fit Scores (FS) are then sent to a human-machine interface and displayed live.

[0014] The following steps can be carried out in detail: - The driver's health factors (GF) are recorded by means of sensors S arranged in a vehicle, for example a commercial vehicle, a bus or passenger car and / or via sensors S in a smartphone or sports wristband. - The driver's health status is determined by an algorithm based on the health factors GF. - The algorithm evaluates individual health factors (GF), weights them, and determines a Fit Score (FS) as a measure of health status. - The state of health is visualized in the form of the Fit Score FS, i.e., displayed on a human-machine interface in the vehicle and / or on the smartphone and / or the sports wristband. - Furthermore, behavioral recommendations (VE) for interventions to improve health status are issued. - A gamification approach should lead to positive feedback on driver behavior FV and thus to a higher Fit-Score FS. - A timeline of the Fit Score (FS) can be viewed.

[0015] The Fit-Score FS is a measure of the driver's health status, determined by sensors S and visually represented. This representation can be done through a graphic designed to playfully motivate the driver to improve their Fit-Score FS, and thus their health, through behavioral adjustments.

[0016] In addition, based on the calculated values, the driver receives behavioral recommendations (VE) to intervene in order to take preventive or health-promoting measures.

[0017] The Fit-Score FS encompasses various health-related health factors (GF) that can be negatively affected by driving. These are recorded by permanently installed sensors (S) in the vehicle's cab and / or by sensors (S), for example, in a smartphone and / or a smartwatch.

[0018] These health factors include: a) Seating variability, b) posture, c) Sitting time, d) Fatigue, e) Drinking and eating habits, f) Stress, g) Joint stress, h) heartbeat, i) Morphological ECG, j) EEG, k) Muscle activity, l) Sleep patterns, m) Physical activity.

[0019] Seat variability describes how still or restless the driver sits. Studies indicate that a person who makes small movements more frequently while sitting experiences less discomfort and therefore sits in a healthier manner. This health factor (GF) can be measured using just a few pressure, force, or acceleration sensors in the seat cushion of a driver's seat.

[0020] Several sensors S can be used to determine body posture. Firstly, the driver's load distribution on the driver's seat can be determined using the sensors S mentioned earlier for determining seat variability. For this purpose, additional sensors S in or on the seat are used to measure the seat position. Furthermore, the driver's mass is relevant. This can be determined either through self-reporting by the driver or via pressure sensors in the cabin floor or in steps leading up to the cabin. Additionally, camera-based sensors S that detect the driver can be used. The body posture can then be calculated from the data of all these sensors S.

[0021] The sitting time can be determined via the aforementioned sensors S in the seat cushion.

[0022] Fatigue can be detected using a combination of camera sensors and sensors embedded in the seat cushion. Camera sensors recognize typical behavioral signs of fatigue, primarily in the face, based on eye movement, head posture, and facial expression. Seat sensors can also provide information about whole-body movements to improve fatigue detection. Furthermore, EEG electrodes can be sewn into the driver's headgear to measure brain activity, providing even more accurate results.

[0023] Drinking and eating habits can be recorded via cameras. It could also be recorded, for example, whether the driver smokes or does something similar.

[0024] Stress can also be detected by camera sensors based on facial expressions indicating emotions, and / or based on cardiovascular function and / or other factors. This can be achieved using camera sensors and / or heart rate sensors in the steering wheel and / or ECG sensors in the driver's clothing.

[0025] The driver's joint load can be calculated based on posture, mass, proportions, and seat settings. This is achieved using sensors in the seat, particularly in the seat cushion, and cameras. The loads on the neck, back, hips, and knees are of particular importance.

[0026] The heartbeat can be detected via sensors S in the steering wheel and / or a heart rate monitor and / or a chest strap and / or ECG sensors in the clothing and / or other means.

[0027] A morphological ECG can be recorded using ECG electrodes integrated into the driver's clothing to derive health-related information.

[0028] To determine the EEG, EEG electrodes can be used in the driver's headgear to obtain information about mood, attention, and other areas.

[0029] To determine muscle activity, EMG electrodes attached to the driver's skin can be used to obtain information about tension and muscular imbalances.

[0030] To determine sleep patterns, heart rate and body movements during sleep can be recorded while the driver is lying in bed, which may be located in the cabin, for example. A heart rate monitor, camera sensors, and / or pressure sensors in the bed can be used for this purpose.

[0031] Physical activity can be determined using a heart rate monitor and / or a chest strap based on a detected heart rate.

[0032] The Fit Score (FS) is calculated by determining all available health factors (GF) and expressing each one as a number, for example, from 1 for poor to 100 for excellent. The health factors (GF) are then weighted to obtain an overall Fit Score. Alternatively, multiple subcategories with their own Fit Scores (FS) are also possible.

[0033] The overall fit score or the fit scores (FS) of the subcategories are displayed on the human-machine interface, for example, on at least one display of a console. The fit score (FS) can be displayed as a diagram, specifically as a semicircle diagram, combined diagram, process diagram, time series, ternary contour diagram, waterfall diagram, pie chart, age pyramid, grouped bar chart, process cycle, partial image diagram, pyramid diagram, circular bar chart, candlestick chart, radial histogram, compressed pie chart, progress bar, linear process diagram, polar diagram, spline diagram, cartogram, triangular bar chart, compressed column chart, or area chart.

[0034] Furthermore, there are various options for where, how often, how large, or how detailed the Fit-Score FS should be displayed. For example, a display behind the steering wheel, selectable by the driver, could show the Fit-Score FS at a glance along with some key information. Additionally, a small, fixed display, perhaps a number, could be shown on a second screen next to the driver, with very detailed information accessible via an app, for example, during a break from driving.

[0035] Based on the data from individual health factors (GF), behavioral recommendations (VE) can be issued as intervention suggestions, which could be displayed to the driver via the screen, a light signal (e.g., a lamp or LED), and / or an audible signal. These behavioral recommendations (VE) include, for example, using the seat's mobilization function, a short exercise program, taking a break, or other positive adjustments. Implementing such an intervention would have a positive effect on the relevant health factor(s) (GF), thus increasing the Fit Score (FS). This function can be combined with at least one app for a smartphone, fitness watch, or other device to create more options and incentives.

[0036] Furthermore, the psychological effect of gamification can be utilized. The aim is to stimulate the driver's competitive spirit and thus playfully promote better health. By using a scoring system and a playful, graphical representation, the driver is motivated to continuously increase their Fit Score (FS). This can be further enhanced by expanding the Fit Score (FS) with levels or comparison lists between multiple drivers. Reference symbol list FS Fit Score FV Driver Behavior GF Health Factors I Input O Output S Sensor, Sensor technology VE behavioral recommendations QUOTES INCLUDED IN THE DESCRIPTION

[0000] This list of documents cited by the applicant was automatically generated and is included solely for the reader's convenience. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions. Cited patent literature

[0000] WO 2016 / 070981 A1

[0003]

Claims

[1] A method for assessing the health of a driver of a motor vehicle, wherein a driver's behavior (FV) is described by health factors (GF) of the driver, which are determined by sensors (S) arranged in the motor vehicle and / or in a smartphone and / or sports bracelet, wherein the health factors (GF) are evaluated and weighted in order to determine at least one fit score (FS) as a measure of the driver's health and to output it on at least one human-machine interface in the motor vehicle and / or on the smartphone and / or on the sports bracelet, wherein behavioral recommendations (VE) for improving the fit score (FS) are generated and output on the human-machine interface, characterized by that a gamification approach is used to increase the fit score (FS), whereby a temporal progression of the fit score (FS) is displayed on the human-machine interface. [2] Method according to claim 1, characterized bythat a graphic is displayed as a gamification approach to motivate the driver in a playful way to improve the fit score (FS) and thus his health through behavioral adjustments. [3] Method according to claim 1 or 2, characterized by that the health factors (GF) include at least one of the following: a) Seat variability, b) posture, c) sitting time, d) tiredness, e) drinking and eating habits, f) stress, g) joint stress, h) heartbeat, i) Morphological ECG, j) EEG, k) muscle activity, l) sleep behavior, m) Physical activity. [4] Method according to one of the preceding claims, characterized by that the behavioral recommendations (VE) include the use of a mobilization function of the seat, a short sports program or a break. [5] Method according to one of the preceding claims, characterized by that several of the following sensors (S) are used: - a pressure, force and / or acceleration sensor in a seat cushion of a driver's seat, - a sensor (S) in or on the driver's seat for measuring a seat adjustment, - a pressure sensor in the floor of a cabin of the motor vehicle or in a step leading to the cabin, - a camera-based sensor (S) for detecting the driver, - EEG electrodes sewn into the driver’s headgear, - Sensors (S) for detecting the heartbeat in the steering wheel, - ECG sensors in the driver’s clothing, - a heart rate monitor and / or chest strap, - EMG electrodes attached to the driver’s skin, - Pressure sensors in a driver's bed.

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