Integrated armrest intelligent closestool control method applied to intelligent home system

Abstract

The invention relates to the technical field of man-machine interaction, in particular to an integrated handrail intelligent closestool control method applied to an intelligent home system, which comprises the following steps: acquiring handrail conductivity and light intensity change signals, screening continuous sections in the same change direction to generate a signal group, comparing signal change to identify a starting command and a quitting command; extracting a user action feature set in combination with closestool operation records, monitoring an armrest angle and a seat ring temperature to judge whether the range is exceeded and adjusting, calling a closestool unit to execute an instruction and monitoring a response state, and generating a unified control result. High-precision contact judgment is achieved by establishing a synchronous feature recognition mechanism of conductance and light reflection signals, triggering recognition is enhanced through signal direction comparison, individualized control is achieved by extracting behavior rules, a self-balancing adjustment mode is constructed in combination with angle and temperature monitoring, control has the self-learning characteristic, response is executed in an integrated mode, and the control precision is improved. Therefore, the sequence time delay is controllable, multi-signal fusion closed-loop control is formed, and the operation continuity and the self-adaptive capability are improved.

Description

Technical Field

[0001] This invention relates to the field of human-computer interaction technology, and in particular to an integrated handrail smart toilet control method applied to smart home systems. Background Technology

[0002] The field of human-computer interaction technology encompasses multi-dimensional information interaction methods based on sensor recognition, voice control, gesture recognition, environmental response, and device linkage, enabling natural communication and command control between users and electronic devices. The core of this technology lies in perceiving user intentions through multi-source information acquisition devices and using control logic to achieve coordinated responses from home devices, thereby realizing intelligent management of the environment, devices, and system operating status. Its overall technical system includes an input perception layer, an interaction recognition layer, and a control execution layer, enabling interactive operations of smart terminals in residential, medical, and elderly care scenarios through voice commands, body movements, or touch control.

[0003] One such integrated smart toilet control method for smart home systems involves integrating the handrail structure with the toilet control system to achieve intelligent operation of toilet functions. Addressing user needs for multiple functions during toilet use, such as washing, drying, seat temperature adjustment, and flushing water pressure control, the method employs multiple sensors to detect user posture information. User commands are received through a touch recognition unit embedded in the handrail surface and a voice input device. Based on the input signals, corresponding control execution programs are triggered to achieve coordinated control of the water valve, seat heating element, and air nozzle, thus forming a multi-channel human-machine interaction control method for smart home systems.

[0004] Existing technologies rely on multi-source sensing input to achieve command recognition. However, they lack time consistency analysis between signals, making them prone to recognition deviations due to fluctuations in sensing signals or environmental interference. Touch recognition units fail to integrate multi-dimensional signal change characteristics and cannot accurately distinguish between continuous and momentary contact states. Voice and touch command triggering relies on static logic and lacks the ability to dynamically learn the sequence and frequency of actions. Device execution is based on a single response and fails to form an automatic correction mechanism based on state feedback. This results in unstable action transitions, untimely posture adjustments, and lagging temperature control during use, and an overall lack of behavioral correlation analysis and coordinated response capabilities. Summary of the Invention

[0005] To address the technical problems existing in the prior art, this invention provides an integrated smart toilet control method with an integrated grab handle applied to a smart home system. The technical solution is as follows: A method for controlling an integrated smart toilet with a grab handle, applicable to a smart home system, includes the following steps: S1: Acquire the electrical conductivity and light reflection signals of the handrail surface, compare the temporal consistency of the two signals, identify continuous segments of the two signals in the same direction, filter out candidate segments, collect synchronous segments of electrical conductivity and light intensity and perform tag merging, extract the joint hand contact signal, and generate handrail sensing signal group. S2: Compare the direction of change of conductivity and light reflection in the handrail sensing signal group, identify the consistent or opposite intervals, mark the signal with increased conductivity and small change of light reflection as the start signal, and the signal with decreased conductivity and large change of light reflection as the exit signal, and generate the handrail command recognition result. S3: Based on the trigger signal in the handrail command recognition result, call the toilet main control unit to record the seat heating, flushing water flow and drying wind speed operation, analyze the user's action sequence and frequency, identify repetitive patterns and extract the action set of usage patterns, and generate handrail action feature set; S4: Based on the user operation mode and behavior characteristics in the handrail action feature set, monitor the changes in handrail angle and seat temperature, determine whether the changes in angle and temperature are within the posture and heating range, and if they are outside the range, adjust the angle and heating power to restore the predetermined state and generate the handrail control execution sequence.

[0006] As a further aspect of the present invention, the handrail sensing signal group includes conductivity change characteristics, light reflection characteristics, and hand contact characteristics; the handrail command recognition result includes start signal characteristics, exit signal characteristics, and trigger interval characteristics; the handrail action feature set includes operation mode characteristics, behavior pattern characteristics, and action sequence characteristics; and the handrail control execution sequence includes angle adjustment characteristics, temperature control characteristics, and posture correction characteristics.

[0007] As a further aspect of the present invention, the step of acquiring the handrail sensing signal group is as follows: S101: Acquire the conductivity change signal generated by the skin induction pad on the handrail surface and the light intensity change signal received by the reflected light receiving window, detect the sampling change of the two sets of signals on the same time axis, calculate the rate of change of adjacent sampling points and match the time period, compare the consistency of the change direction of conductivity and light intensity, and generate the time consistency comparison result. S102: Based on the time consistency comparison results, select continuous segments where the conductivity and light intensity change in the same direction during the same time period, calculate the upper and lower bounds of amplitude fluctuations and combine them with the time difference between adjacent sampling points to judge signal stability, and remove segments whose fluctuations exceed the set conductivity fluctuation threshold to obtain a set of low-noise continuous segments. S103: Based on the set of low-noise continuous segments, synchronous segments of conductivity and light intensity are collected in chronological order within the corresponding time range, the tags are merged, the joint change characteristics of the two sets of signals in the synchronous segment are extracted, and the combined signal strength is calculated by combining the duration and amplitude stability to generate the handrail sensing signal group.

[0008] As a further aspect of the present invention, the step of obtaining the handrail command recognition result is as follows: S201: Based on the conductivity change signal and light reflection signal sequence in the handrail sensing signal group, detect the corresponding segments of the two signal groups on the time axis, calculate the rate of change of adjacent sampling points and compare their change directions, identify the intervals with the same or opposite change directions in the same time period, and obtain the signal direction corresponding interval set. S202: Based on the interval set corresponding to the signal direction, extract the change amplitude of the conductance change signal within the same interval, calculate the amplitude difference of the light reflection signal within the same interval, determine whether the amplitude difference of the light reflection signal exceeds a set threshold, distinguish the intervals with amplitudes below the threshold and those exceeding the threshold, and generate signal amplitude classification results. S203: Based on the signal amplitude classification results, select the intervals where the conductivity change is enhanced and the light reflection amplitude is lower than the set threshold and mark them as start signals; select the intervals where the conductivity change is weakened and the light reflection amplitude exceeds the threshold and mark them as exit signals; integrate the time stamp and amplitude information of the two types of signals to generate handrail command recognition results.

[0009] As a further aspect of the present invention, the step of obtaining the handrail motion feature set is as follows: S301: Based on the trigger signal in the handrail command recognition result, call the operation data such as seat heating, flushing water flow and drying wind speed recorded by the toilet main control unit, extract the operation records of different use stages, obtain the execution order of control behavior in each stage, record and organize the changes of each control behavior combination in different time periods, and generate operation behavior records. S302: Based on the operation behavior records, the frequency of occurrence of each control behavior combination within the same time period is statistically analyzed, control behavior combinations with a frequency higher than a set threshold are selected, common operation modes are identified, and the trigger signals and behavior execution processes of each mode are integrated to obtain a set of common operation modes. S303: Based on the set of common operation modes, analyze the continuity and consistency of control behavior in the operation sequence, and extract the set of actions that can represent the user's long-term usage patterns by comparing the time continuity of different operation modes, and generate the handrail action feature set.

[0010] As a further aspect of the present invention, the step of obtaining the handrail control execution sequence is as follows: S401: Based on the user operation mode and behavior characteristics in the handrail action feature set, obtain the angle change of the handrail angle detection rod and the temperature change of the seat temperature sensing pad, compare the angle change data with the posture reference range, determine the degree of angle deviation from the reference value, calculate the average offset value of the continuous deviation range, and generate the posture offset degree. S402: Based on the attitude offset, analyze the temperature change trend of the temperature sensing patch, calculate the temperature gradient of the continuous sampling interval, and determine whether the temperature change conforms to the heating range. Combine the time period of the angle offset to obtain the heating stability. S403: Based on the relationship between the posture offset and the heating stability, determine whether the angle exceeds the normal range, adjust the seat ring heating power according to the temperature fluctuation, and calculate the adjusted angle and heating power to generate the armrest control execution sequence.

[0011] As a further aspect of the present invention, the method further includes: S5: Based on the instruction information in the handrail control execution sequence, call the action ports of the flushing unit, drying unit and seat lifting unit in the toilet main control unit, execute the instructions in sequence and monitor the response status, confirm that the order and duration of the execution process meet the preset requirements, integrate the execution status, and generate the handrail smart toilet control result; The control results of the smart toilet with armrests include flushing control features, drying control features, and lifting control features.

[0012] As a further aspect of the present invention, the step of obtaining the control result of the smart toilet with armrest is as follows: S501: Obtain instruction information in the armrest control execution sequence, parse the action port numbers and instruction types of the rinsing unit, drying unit and seat ring lifting unit, record the start signal time point and duration parameters of each action port, calculate the time interval value between adjacent instructions, and generate an instruction timing parameter set; S502: According to the instruction timing parameter set, the toilet main control unit is called to send execution signals to each action port in sequence, monitor the response feedback signal amplitude and feedback time of the flushing, drying and lifting units, calculate the difference between the feedback time and the corresponding instruction interval, and determine whether the signal feedback is continuous and effective, so as to obtain the action response difference sequence. S503: Based on the action response difference sequence, compare the execution order, feedback duration and response interval of each action port, calculate the execution order deviation rate and action duration offset, integrate the quantitative data of the order deviation rate and feedback difference, establish a unified control output parameter set, and generate the control result of the smart toilet with handrail.

[0013] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: In this invention, a synchronous feature recognition mechanism is formed by establishing a time correspondence between electrical conductivity and light reflection signals, thereby achieving high-precision judgment of the contact state. The accuracy and stability of trigger recognition are enhanced by comparing signal direction correlations. Individualized control response is achieved by extracting action patterns from behavioral frequency and sequence features. Combined with dynamic monitoring of angle and temperature trends, a self-balancing adjustment mode for attitude and heating power is constructed, enabling the control process to have self-learning and self-repair characteristics. The execution layer response signals are integrated and output to maintain sequential consistency and controllable delay. A closed-loop control structure is formed in terms of multi-signal fusion, behavioral correlation recognition, and dynamic execution coordination, thereby improving operational continuity and system adaptability. Attached Figure Description

[0014] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a flowchart illustrating the acquisition process of the handrail sensor signal group in this invention. Figure 3 This is a flowchart illustrating the process of obtaining the handrail command recognition result according to the present invention. Figure 4 This is a flowchart illustrating the process of obtaining the handrail motion feature set according to the present invention. Figure 5 This is a flowchart illustrating the process of obtaining the handrail control execution sequence of the present invention. Figure 6 This is a flowchart illustrating the process of obtaining the control results of the smart toilet with handrail according to the present invention. Detailed Implementation

[0015] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0016] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0017] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0018] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0019] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0020] Please see Figure 1 This invention provides a technical solution: an integrated smart toilet control method for handrails applied to a smart home system, comprising the following steps: S1: Acquire the conductivity change signal generated by the skin induction pad on the handrail surface and the light intensity change signal received by the handrail reflection light receiving window. Record the corresponding change segments of the conductivity change signal and the light intensity change signal in time. Compare the temporal consistency between the conductivity change trend and the light reflection change trend. Identify continuous segments where the conductivity change signal and the light intensity change signal maintain the same change direction in the same time period. Based on the upper and lower limits of amplitude fluctuation and the stability judgment of adjacent sampling intervals, select candidate segments from the continuous segments with noise below the set threshold and meeting the duration requirements. In the candidate segments, collect the synchronous segments of conductivity and light intensity in chronological order and perform label merging. Extract the joint signal set that can characterize the hand contact state and generate the handrail sensing signal group. S2: Based on the electrical conductivity change signal and light reflection signal sequence in the handrail sensing signal group, the change direction of the skin electrical conductivity change signal and the light reflection signal is compared segment by segment to identify the intervals where the electrical conductivity change signal and the light reflection signal are consistent or opposite in time. The trigger type corresponding to each consistent interval is determined, and the interval where the skin electrical conductivity change is enhanced and the change amplitude of the light reflection signal is lower than the set threshold is marked as the start signal, and the interval where the skin electrical conductivity change is weakened and the change amplitude of the light reflection signal exceeds the set threshold is marked as the exit signal, generating the handrail command recognition result; S3: Based on the trigger signal in the handrail command recognition result, call the operation records of seat heating, flushing water flow and drying air speed recorded by the toilet main control unit, analyze the user's action sequence at different usage stages, identify frequently repeated operation patterns, record control behavior combinations that occur more frequently than a set threshold within the same time period, and extract action sets that represent long-term usage patterns based on the continuity and consistency of the operation sequence to generate handrail action feature set; S4: Based on the user operation patterns and behavioral characteristics of the armrest action feature set, monitor the angle change trend of the armrest angle detection rod and the temperature change trend of the seat temperature sensing pad, determine whether the angle change is within the posture range of the action set, and determine whether the temperature change is within the heating range of the action set. If the angle change exceeds the normal range, adjust the armrest angle to restore the predetermined posture. If the temperature change exceeds the set heating range, adjust the seat heating power to restore a comfortable temperature and generate an armrest control execution sequence. S5: Based on the instruction information in the handrail control execution sequence, call the action ports of the flushing unit, drying unit and seat lifting unit in the toilet main control unit, execute the instructions in sequence and monitor the response status of the executed actions, confirm that the order of the execution process and the duration of each action meet the preset time interval and sequence requirements, integrate all execution statuses into a unified control output, and generate the handrail smart toilet control result.

[0021] The handrail sensing signal set includes electrical conductivity change characteristics, light reflection characteristics, and hand contact characteristics. The handrail command recognition results include start signal characteristics, exit signal characteristics, and trigger interval characteristics. The handrail action feature set includes operation mode characteristics, behavior pattern characteristics, and action sequence characteristics. The handrail control execution sequence includes angle adjustment characteristics, temperature control characteristics, and posture correction characteristics. The handrail smart toilet control results include flushing control characteristics, drying control characteristics, and lifting control characteristics.

[0022] Please see Figure 2 The steps for acquiring the handrail sensor signal group are as follows: S101: Acquire the conductivity change signal generated by the skin induction pad on the handrail surface and the light intensity change signal received by the reflected light receiving window, detect the sampling change of the two sets of signals on the same time axis, calculate the rate of change of adjacent sampling points and match the time period, compare the consistency of the change direction of conductivity and light intensity, and generate the time consistency comparison result. The conductivity change signal generated by the skin inductive pad on the handrail surface was obtained. The light intensity change signal received by the reflected light receiving window The original sampling data; Table 1: Original Signal Sampling Table of Handrail Sensor

[0023] As shown in Table 1, the sampling changes of two sets of signals are detected on a unified time axis, for example, at time point T=1. , At time point T=2, , Calculate the rate of change of adjacent sampling points during the time interval from T=1 to T=2. rate of change , rate of change Match the time period [T=1, T=2] and compare the consistency of the change direction of conductivity and light intensity, including the direction of conductivity change. (Decrease), direction of light intensity change (Enhanced), the two change in different directions, so we continue to calculate the time period from T=2 to T=3. , , , Since the directions of change are inconsistent, we continue calculating the time interval from T=5 to T=6. , , , The two changes in the same direction, so [T=5, T=6] is marked as "consistent". Continue calculating the time interval from T=6 to T=7. , , , Mark [T=6, T=7] as "consistent", and continue calculating the time interval from T=7 to T=8. , , , Mark [T=7,T=8] as "consistent", perform the comparison on all time periods [T=1,T=10], and generate time consistency comparison results.

[0024] S102: Based on the time consistency comparison results, select continuous segments where the conductivity and light intensity change in the same direction during the same time period, calculate the upper and lower bounds of amplitude fluctuations and judge signal stability by combining the time difference between adjacent sampling points, and remove segments whose fluctuations exceed the set conductivity fluctuation threshold to obtain a set of low-noise continuous segments. Based on the time consistency comparison results, the results include segments marked as "consistent" [T=5,T=6], [T=6,T=7], and [T=7,T=8], as well as other segments marked as "inconsistent". Continuous segments where conductivity and light intensity change in the same direction within the same time period are selected to identify these continuous segments. Calculate the range within this section The upper and lower bounds of the signal amplitude fluctuation. The set of signal readings in the range [T=5, T=8] is as follows , , amplitude fluctuation ,calculate The upper and lower bounds of the signal amplitude fluctuation. The signal reading set is , , amplitude fluctuation Signal stability is determined by combining the time difference between adjacent sampling points. The fixed sampling interval of 1 second indicates that the signal acquisition is stable, and the conductivity fluctuation threshold is set. The threshold Based on 200 noise tests conducted with the hand suspended in the air without contacting the sensor, the maximum conductance fluctuation observed during the tests was determined. ,set up Remove segments whose fluctuations exceed the set conductivity fluctuation threshold, and compare the segments. fluctuations , Section If another "consistent" segment exists, it will be retained. ,That The signal set is ,That , Then the section These will be removed, resulting in a set of low-noise continuous segments.

[0025] S103: Based on the set of low-noise continuous segments, synchronous segments of conductivity and light intensity are collected in time sequence within the corresponding time range, the tags are merged, the joint change characteristics of the two sets of signals in the synchronous segment are extracted, and the combined signal strength is calculated by combining duration and amplitude stability to generate handrail sensing signal group. Based on the set of low-noise continuous segments, the current set contains segments. Synchronous segments of conductivity and light intensity are collected in chronological order within the corresponding time range [T=5, T=8] to obtain the segments. Perform tag merging and sort the fragments. Marked as SyncFrag_001, extract the joint variation characteristics of the two sets of signals within the synchronization segment. In SyncFrag_001... The characteristics of signal changes are ="Increase first, then decrease" (6.5->7.0->6.5) The characteristics of signal changes are ="Increase first, then decrease" (780->785->770), combining duration and amplitude stability to calculate the combined signal strength, duration Amplitude stability (by (Signal fluctuation reciprocal) Set duration benchmark and amplitude stability benchmark (corresponding fluctuations) ), set weights and Combined signal strength The intensity value of 3.4 is associated with SyncFrag_001 to generate a handrail sensing signal group.

[0026] Please see Figure 3 The steps for obtaining the handrail command recognition result are as follows: S201: Based on the conductivity change signal and light reflection signal sequence in the handrail sensing signal group, detect the corresponding segments of the two signal groups on the time axis, calculate the rate of change of adjacent sampling points and compare their change directions, identify the intervals with the same or opposite change directions in the same time period, and obtain the signal direction corresponding interval set. Based on the handrail sensing signal group, which includes SyncFrag_001 (time [T=5,T=8], intensity 3.4), and simultaneously calling the complete original sequence in Table 1, the corresponding segments of the two signal groups on the time axis are detected. Segment 1 is [T=5,T=8], segment 2 is [T=1,T=5], etc. The rate of change of adjacent sampling points is calculated and their direction of change is compared. For segment 1 [T=5,T=8], [T=5,T=6]: ,direction , The result is determined to be "consistent", [T=6,T=7]: ,direction , The result is determined to be "consistent", [T=7,T=8]: ,direction , The result is determined to be "consistent" for segment 2 [T=2,T=5] and [T=2,T=3]: ,direction , The result is determined to be "opposite", [T=3,T=4]: ,direction , The result is determined to be "opposite", [T=4,T=5]: ,direction , If the signal is determined to be "opposite", the intervals with the same or opposite direction of change within the same time period are identified. The continuous intervals with the same direction are identified as IntA=[T=5,T=8], and the continuous intervals with the opposite direction are identified as IntB=[T=2,T=5], thus obtaining the interval set corresponding to the signal direction.

[0027] S202: Based on the interval set corresponding to the signal direction, extract the change amplitude of the conductance change signal within the same interval, calculate the amplitude difference of the light reflection signal within the same interval, determine whether the amplitude difference of the light reflection signal exceeds the set threshold, distinguish the intervals with amplitudes below the threshold and those exceeding the threshold, and generate signal amplitude classification results. Based on the signal direction corresponding interval set, which contains {IntA:[T=5,T=8], type: "consistent"} and {IntB:[T=2,T=5], type: "opposite"}, the amplitude of the conductance change signal within the consistent interval is extracted. For IntA, it is further subdivided into [T=5,T=7](...). (enhanced) and [T=7,T=8]( (weakening), [T=5,T=7] range of change [T=7,T=8] range of change And calculate the amplitude difference of the reflected light signal within the same interval, [T=5, T=7]. Amplitude difference Its absolute magnitude [T=7,T=8] Amplitude difference Its absolute magnitude Set the threshold for the amplitude difference of the light reflection signal. The threshold It is used to distinguish between slight touch (small change in light signal) and hand removal (large change in light signal), and is tested through 100 touch cycles. The mean is 100 removal tests, its The mean is ,set up Determine whether the amplitude difference of the reflected light signal exceeds a set threshold, within the range [T=5, T=7]: , The condition is determined to be "below the threshold", within the interval [T=7, T=8]: , The condition is determined to be "below the threshold", and the interval IntB[T=2,T=5] is analyzed. (Enhancement), its Amplitude difference Its absolute magnitude , The signal amplitude is determined to be "exceeding the threshold", and the ranges below and above the threshold are distinguished to generate signal amplitude classification results.

[0028] S203: Based on the signal amplitude classification results, filter out the intervals where the conductivity change is enhanced and the light reflection amplitude is lower than the set threshold and mark them as start signals; filter out the intervals where the conductivity change is weakened and the light reflection amplitude exceeds the threshold and mark them as exit signals; integrate the time stamp and amplitude information of the two types of signals to generate handrail command recognition results. Based on the signal amplitude classification results, which include {[T=5,T=7]: "below threshold"}, {[T=7,T=8]: "below threshold"}, and {[T=2,T=5]: "above threshold"}, the intervals with increased conductivity changes and light reflection amplitudes below the set threshold are filtered out. The interval [T=5,T=7] is then examined. range of change (Increased change in conductivity), its The amplitude is classified as "below the threshold," meeting the condition, and marked as the start signal Sig_Start_001. The check interval [T=7, T=8] is... range of change (The change in conductivity weakens), which does not meet the conditions. Check the interval [T=2, T=5]. range of change (Increased change in conductivity), its The amplitude is classified as "exceeding the threshold," which does not meet the criteria. Therefore, the intervals where the conductivity change weakens and the light reflection amplitude exceeds the threshold are selected. The interval [T=7, T=8] is then examined. The change weakened, but The amplitude is "below the threshold," which does not meet the condition. Therefore, data from Table 1 [T=8, T=9] is retrieved. change (The change in conductivity weakens), its change , , (Amplitude exceeds the threshold), meets the condition, and is marked as an exit signal Sig_Exit_001. The time identifier and amplitude information of the two types of signals are integrated. Sig_Start_001 corresponds to time [T=5,T=7], and Sig_Exit_001 corresponds to time [T=8,T=9], generating the handrail command recognition result.

[0029] Please see Figure 4 The steps for obtaining the handrail motion feature set are as follows: S301: Based on the trigger signal in the handrail command recognition result, call the operation data such as seat heating, flushing water flow and drying air speed recorded by the toilet main control unit, extract the operation records of different use stages, obtain the execution sequence of control behavior in each stage, record and organize the changes of each control behavior combination in different time periods, and generate operation behavior records. Based on the trigger signal in the handrail command recognition result, which includes Sig_Start_001 (T=5) and Sig_Exit_001 (T=8), the operation data such as seat heating, flushing water flow and drying air speed recorded by the toilet main control unit are called. Table 2: Toilet Main Control Unit Operation Record Sheet

[0030] As shown in Table 2, operation records for different usage stages are extracted. Stage 1 starts with Sig_Start_001 (T=5.0) and ends with Sig_Exit_001 (T=90.0). The execution order of control behaviors within each stage is obtained. The order for Stage 1 is as follows: Phase 2 begins with Sig_Start_002 (T=100.0) and ends with Sig_Exit_002 (T=200.0). The sequence of Phase 2 is as follows: Record and organize the changes of each control behavior combination over different time periods to generate an operational behavior record.

[0031] S302: Based on the operation behavior record, the frequency of occurrence of each control behavior combination within the same time period is statistically analyzed, control behavior combinations with a frequency higher than a set threshold are filtered out, common operation modes are identified, and the trigger signals and behavior execution processes of each mode are integrated to obtain a set of common operation modes. Based on the operation behavior record, this record contains and And (assuming) another 48 historical session records, totaling The frequency of occurrence of each combination of control behaviors within the same time period was statistically analyzed. and We discovered a common set of control behaviors (subsequences). ,statistics Frequency of occurrence in all 50 sessions This time, another combination was counted simultaneously. its frequency Next, select control behavior combinations that occur more frequently than a set threshold, and set the frequency threshold. The threshold Set to total number of sessions A percentage, for example , Next, comparison frequency, , Selected, Compare frequency, , Removed, identified For common operating modes, the trigger signals and behavior execution processes of each mode are integrated. Triggered by Sig_Start_..., the execution process is as follows: This yields a set of common operation modes.

[0032] S303: Based on the set of common operation modes, analyze the continuity and consistency of control behavior in the operation sequence, and extract the set of actions that can represent the long-term usage patterns of users by comparing the time continuity of different operation modes, and generate the handrail action feature set. Based on a set of common operating modes, this set contains modes Analyze the persistence and consistency of control behavior in the sequence of operations, and analyze middle The duration of heating (T=5.0) to drying (T=60.0), total duration ,analyze middle The duration of the process, from "heating" (T=100.0) to "drying" (T=165.0), is the total duration. ,analyze The parameter consistency was such that the "heating" parameter appeared 35 times out of 35 occurrences. (consistency The "rinsing" parameter was consistently set to intensity 3 for all 35 rinses (consistency). The "drying" parameter was the same for all 35 tests. (consistency By comparing the time continuity of different operating modes, the calculation is performed. Average duration Assuming the mean is the calculation duration Calculate the standard deviation of duration , Assuming ,set up , This indicates a high degree of consistency in time continuity, allowing for the extraction of a set of actions that represent long-term user behavior patterns. Include pattern sequence, parameters and time characteristics Generate a set of handrail motion features.

[0033] Please see Figure 5 The steps for obtaining the handrail control execution sequence are as follows: S401: Based on the user operation patterns and behavioral characteristics of the armrest action feature set, obtain the angle change of the armrest angle detection rod and the temperature change of the seat temperature sensing pad, compare the angle change data with the posture reference range, determine the degree of angle deviation from the reference value, calculate the average offset value of the continuous deviation range, and generate the posture offset degree. Based on user operation patterns and behavioral characteristics within the handrail action feature set, this feature set includes The system acquires the angle change of the armrest angle detection rod and the temperature change of the seat temperature sensing pad, and triggers Sig_Start_101 (matching) when the user activates it. After (mode), the system detects the current handrail angle. Current seat temperature Based on the comparison between angle change data and attitude reference range, the attitude reference range is... according to Historical data (50 sessions) statistics settings for the mode. Assuming historical average perspective Standard deviation ,but To determine the degree to which the angle deviates from the reference value. Exceeding The upper realm deviation The average offset value of the continuous deviation interval is calculated, and the angle is continuously monitored within [T=0, T=2s]. average angle Average offset value Generate attitude offset.

[0034] S402: Based on the attitude offset, analyze the temperature change trend of the temperature sensing patch, calculate the temperature gradient of the continuous sampling interval, and determine whether the temperature change conforms to the heating range. Combine the time period of the angle offset to obtain the heating stability. Based on the attitude offset, this offset Analyze the temperature change trend of the temperature sensing patch, current temperature Monitor the temperature within [T=0, T=2s]. Calculate the temperature gradient at consecutive sampling intervals, sampling interval average gradient And determine whether the temperature change conforms to the heating range. according to mode parameters set up, (allow (fluctuations), current temperature It does not conform to the heating range. A comparison is made based on the time period of angle offset; within the time period [T=0, T=2s], (There is an offset) and (Insufficient temperature) , heating stability is obtained, heating stability Defined as the difference between the current temperature and the target lower limit. The heating stability was obtained.

[0035] S403: Based on the relationship between posture deviation and heating stability, determine whether the angle exceeds the normal range, adjust the seat ring heating power according to temperature fluctuations, calculate the adjusted angle and heating power, and generate the armrest control execution sequence. Based on attitude offset and heating stability The relationship is used to determine whether the angle exceeds the normal range. Confirm that the angle is outside the normal range. And based on temperature fluctuations (i.e. (Temperature deficit) Adjust seat heating power; current heating power Adjustment amount and Proportional heating coefficient Based on experimental data on the heat capacity and heat dissipation of the seat ring material, it was set as follows: , Calculate the adjusted angle and heating power, and the adjusted target angle. (Right now (upper limit), angle adjustment command Adjusted heating power Generate the handrail control execution sequence.

[0036] Please see Figure 6 The steps for obtaining the control results of the smart toilet with handrail are as follows: S501: Obtain instruction information in the armrest control execution sequence, parse the action port numbers and instruction types of the washing unit, drying unit and seat ring lifting unit, record the start signal time point and duration parameters of each action port, calculate the time interval value between adjacent instructions, and generate an instruction timing parameter set; Obtain instruction information from the handrail control execution sequence, which contains The operation port numbers and command types of the rinsing unit, drying unit, and seat ring lifting unit are analyzed. The corresponding action port Port01 of the seat ring lifting unit (angle motor) has a command type of 0x0A (relative movement). The corresponding operating port Port02 of the seat ring heating unit has an instruction type of 0x0B (set power). Table 3: Handrail Control Execution Sequence Instruction Table

[0037] As shown in Table 3, the command data -250 represents -2.50 degrees, and the command data 212 represents... (assumption) ,but Record the start signal time and duration parameters of each action port, C001 (angle) start time. According to the motor speed Calculate duration C002 (heating) start-up time Duration (Next monitoring cycle) Calculate the time interval between adjacent commands. Generate instruction timing parameter set.

[0038] S502: Based on the instruction timing parameter set, the toilet main control unit is called to send execution signals to each action port in sequence, monitor the response feedback signal amplitude and feedback time of the flushing, drying and lifting units, calculate the difference between the feedback time and the corresponding instruction interval, and determine whether the signal feedback is continuous and effective, and obtain the action response difference sequence. Based on the instruction timing parameter set, which includes {C001:Start=0.0s,Dur=2.5s} and {C002:Start=0.1s,Dur=60s}, the toilet master control unit is invoked to send execution signals sequentially to each action port. At T=0.0s, C001 is sent to Port_01, and at T=0.1s, C002 is sent to Port_02. The amplitude and time of the response feedback signals from the flushing, drying, and lifting units are monitored. Port_01 sends an ACK signal (5V amplitude) at T=0.15s and a DONE signal (5V amplitude) at T=2.8s. Port_02 sends an ACK signal (5V amplitude) at T=0.2s. The difference between the feedback time and the corresponding instruction interval is calculated to determine the actual duration of C001's action. (Assuming the ACK time is the startup time), and the expected duration. The difference The difference in startup response of C002 The system determines whether the signal feedback (5VACK / DONE) is continuously valid. If the amplitudes of both signals are within the valid range [4.5V, 5.5V], they are determined to be continuously valid, and the action response difference sequence is obtained.

[0039] S503: Based on the action response difference sequence, the execution order, feedback duration and response interval of each action port are compared, the execution order deviation rate and action duration offset are calculated, the quantitative data of the order deviation rate and feedback difference are integrated, a unified control output parameter set is established, and the control result of the smart toilet with handrail is generated. Based on the action response difference sequence, this sequence contains The execution order, feedback duration, and response interval of each action port are compared. The expected execution order (C001, C002) and the actual response order (C001ACKT=0.15s, C002ACKT=0.2s) are consistent. The expected duration of C001 is 2.5s, and the actual duration is 2.65s. The expected start time of C002 is 0.1s, and the actual response time is 0.2s. The execution order deviation rate and the action duration offset are calculated. Expected order vector (C001 first, C002 second), actual response vector (C001 responds first, C002 responds later). Action duration offset The quantitative data of sequence deviation rate and feedback difference are integrated to form... Establish a unified set of control output parameters to generate control results for the smart toilet with handrail.

[0040] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for controlling an integrated smart toilet with a grab handle applied to a smart home system, characterized in that, Includes the following steps: S1: Acquire the electrical conductivity and light reflection signals of the handrail surface, compare the temporal consistency of the two signals, identify continuous segments of the two signals in the same direction, filter out candidate segments, collect synchronous segments of electrical conductivity and light intensity and perform tag merging, extract the joint hand contact signal, and generate handrail sensing signal group. S2: Compare the direction of change of conductivity and light reflection in the handrail sensing signal group, identify the consistent or opposite intervals, mark the signal with increased conductivity and small change of light reflection as the start signal, and the signal with decreased conductivity and large change of light reflection as the exit signal, and generate the handrail command recognition result. S3: Based on the trigger signal in the handrail command recognition result, call the toilet main control unit to record the seat heating, flushing water flow and drying wind speed operation, analyze the user's action sequence and frequency, identify repetitive patterns and extract the action set of usage patterns, and generate handrail action feature set; S4: Based on the user operation mode and behavior characteristics in the handrail action feature set, monitor the changes in handrail angle and seat temperature, determine whether the changes in angle and temperature are within the posture and heating range, and if they are outside the range, adjust the angle and heating power to restore the predetermined state and generate the handrail control execution sequence.

2. The integrated handrail smart toilet control method applied to a smart home system according to claim 1, characterized in that: The handrail sensing signal set includes conductivity change characteristics, light reflection characteristics, and hand contact characteristics. The handrail command recognition result includes start signal characteristics, exit signal characteristics, and trigger interval characteristics. The handrail action feature set includes operation mode characteristics, behavior pattern characteristics, and action sequence characteristics. The handrail control execution sequence includes angle adjustment characteristics, temperature control characteristics, and posture correction characteristics.

3. The integrated handrail smart toilet control method applied to a smart home system according to claim 1, characterized in that: The steps for acquiring the handrail sensor signal group are as follows: S101: Acquire the conductivity change signal generated by the skin induction pad on the handrail surface and the light intensity change signal received by the reflected light receiving window, detect the sampling change of the two sets of signals on the same time axis, calculate the rate of change of adjacent sampling points and match the time period, compare the consistency of the change direction of conductivity and light intensity, and generate the time consistency comparison result. S102: Based on the time consistency comparison results, select continuous segments where the conductivity and light intensity change in the same direction during the same time period, calculate the upper and lower bounds of amplitude fluctuations and combine them with the time difference between adjacent sampling points to judge signal stability, and remove segments whose fluctuations exceed the set conductivity fluctuation threshold to obtain a set of low-noise continuous segments. S103: Based on the set of low-noise continuous segments, synchronous segments of conductivity and light intensity are collected in chronological order within the corresponding time range, the tags are merged, the joint change characteristics of the two sets of signals in the synchronous segment are extracted, and the combined signal strength is calculated by combining the duration and amplitude stability to generate the handrail sensing signal group.

4. The integrated handrail smart toilet control method applied to a smart home system according to claim 1, characterized in that: The steps for obtaining the handrail command recognition result are as follows: S201: Based on the conductivity change signal and light reflection signal sequence in the handrail sensing signal group, detect the corresponding segments of the two signal groups on the time axis, calculate the rate of change of adjacent sampling points and compare their change directions, identify the intervals with the same or opposite change directions in the same time period, and obtain the signal direction corresponding interval set. S202: Based on the interval set corresponding to the signal direction, extract the change amplitude of the conductance change signal within the same interval, calculate the amplitude difference of the light reflection signal within the same interval, determine whether the amplitude difference of the light reflection signal exceeds a set threshold, distinguish the intervals with amplitudes below the threshold and those exceeding the threshold, and generate signal amplitude classification results. S203: Based on the signal amplitude classification results, select the intervals where the conductivity change is enhanced and the light reflection amplitude is lower than the set threshold and mark them as start signals; select the intervals where the conductivity change is weakened and the light reflection amplitude exceeds the threshold and mark them as exit signals; integrate the time stamp and amplitude information of the two types of signals to generate handrail command recognition results.

5. The integrated smart toilet control method for handrails applied to a smart home system according to claim 1, characterized in that: The steps for obtaining the handrail motion feature set are as follows: S301: Based on the trigger signal in the handrail command recognition result, call the operation data such as seat heating, flushing water flow and drying wind speed recorded by the toilet main control unit, extract the operation records of different use stages, obtain the execution order of control behavior in each stage, record and organize the changes of each control behavior combination in different time periods, and generate operation behavior records. S302: Based on the operation behavior records, the frequency of occurrence of each control behavior combination within the same time period is statistically analyzed, control behavior combinations with a frequency higher than a set threshold are selected, common operation modes are identified, and the trigger signals and behavior execution processes of each mode are integrated to obtain a set of common operation modes. S303: Based on the set of common operation modes, analyze the continuity and consistency of control behavior in the operation sequence, and extract the set of actions that can represent the user's long-term usage patterns by comparing the time continuity of different operation modes, and generate the handrail action feature set.

6. The integrated handrail smart toilet control method applied to a smart home system according to claim 1, characterized in that: The steps for obtaining the handrail control execution sequence are as follows: S401: Based on the user operation mode and behavior characteristics in the handrail action feature set, obtain the angle change of the handrail angle detection rod and the temperature change of the seat temperature sensing pad, compare the angle change data with the posture reference range, determine the degree of angle deviation from the reference value, calculate the average offset value of the continuous deviation range, and generate the posture offset degree. S402: Based on the attitude offset, analyze the temperature change trend of the temperature sensing patch, calculate the temperature gradient of the continuous sampling interval, and determine whether the temperature change conforms to the heating range. Combine the time period of the angle offset to obtain the heating stability. S403: Based on the relationship between the posture offset and the heating stability, determine whether the angle exceeds the normal range, adjust the seat ring heating power according to the temperature fluctuation, and calculate the adjusted angle and heating power to generate the armrest control execution sequence.

7. The integrated smart toilet control method for handrails applied to a smart home system according to claim 1, characterized in that: The method further includes: S5: Based on the instruction information in the handrail control execution sequence, call the action ports of the flushing unit, drying unit and seat lifting unit in the toilet main control unit, execute the instructions in sequence and monitor the response status, confirm that the order and duration of the execution process meet the preset requirements, integrate the execution status, and generate the handrail smart toilet control result; The control results of the smart toilet with armrests include flushing control features, drying control features, and lifting control features.

8. The integrated smart toilet control method for handrails applied to a smart home system according to claim 7, characterized in that: The steps for obtaining the control results of the smart toilet with armrest are as follows: S501: Obtain instruction information in the armrest control execution sequence, parse the action port numbers and instruction types of the rinsing unit, drying unit and seat ring lifting unit, record the start signal time point and duration parameters of each action port, calculate the time interval value between adjacent instructions, and generate an instruction timing parameter set; S502: According to the instruction timing parameter set, the toilet main control unit is called to send execution signals to each action port in sequence, monitor the response feedback signal amplitude and feedback time of the flushing, drying and lifting units, calculate the difference between the feedback time and the corresponding instruction interval, and determine whether the signal feedback is continuous and effective, so as to obtain the action response difference sequence. S503: Based on the action response difference sequence, compare the execution order, feedback duration and response interval of each action port, calculate the execution order deviation rate and action duration offset, integrate the quantitative data of the order deviation rate and feedback difference, establish a unified control output parameter set, and generate the control result of the smart toilet with handrail.

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