99 results about "Physiological responses" patented technology

The invention discloses a neurology patient rehabilitation nursing method based on multi-modal data analysis, and relates to the technical field of medical health, and the method comprises the steps: extracting neural function features through a multi-modal data fusion algorithm, and carrying out the calculation through a weighted fusion and statistical analysis method, and obtaining a neuroplasticity index vector; combining the neuroplasticity index vector with the unified multi-modal feature representation, carrying out multi-modal abnormal mode recognition analysis, obtaining a rehabilitation risk early warning signal and a personalized intervention suggestion, and generating a personalized rehabilitation scheme; performing dynamic optimization and self-adaptive adjustment on the individualized rehabilitation scheme by using a feedback loop mechanism to generate an optimized individualized rehabilitation scheme; physiological signals in individualized rehabilitation training based on the optimized individualized rehabilitation scheme are collected in real time and preprocessed, and a standardized physiological response data sequence is generated. According to the invention, the scientificity, timeliness and individual adaptability of regulation and control are improved, so that nerve function remodeling is accelerated and the rehabilitation risk is reduced.

The invention relates to the technical field of pain assessment, in particular to a paediatric pain assessment system which comprises a muscle group rhythm recognition module, a behavior linkage screening module, a periodic fluctuation extraction module, a behavior physiological difference module and a pain grading judgment module. According to the method, a linkage offset identification path is constructed through an angle relation between facial muscle groups and a starting time sequence, multi-muscle cooperative imbalance performance is identified, a region-level dynamic behavior judgment basis is formed, and a behavior cooperative judgment mechanism is established by utilizing response overlapping conditions of multiple behavior characteristics in the same time period; path signals which do not form effective cooperation are eliminated, the effectiveness of behavior characteristics is enhanced, a continuous trend structure of peak time in rhythm change is introduced, a periodic response sudden change monitoring channel is constructed, the recognition sensitivity of a short-time fluctuation concentration section is improved, and a response mismatch section is extracted based on a trigger time dislocation state between behavior and physiological response, so that the recognition sensitivity of the short-time fluctuation concentration section is improved. And a pain judgment key point is positioned in the time sequence overlapping region.

The invention discloses an intelligent data labeling method based on artificial intelligence, and relates to the technical field of intelligent medical treatment, and the method comprises the following steps: obtaining physiological parameter data, historical health parameter data and motion state data of a user; outputting motion state label data through a pre-constructed motion recognition model according to the motion state data; and performing sliding window analysis on the historical health parameter data, and dynamically establishing and updating long-term change data of the user health parameters. According to the scheme, whether the physiological parameter fluctuation is caused by the movement or not can be distinguished through associated retrieval of time window division and the movement state label, for example, when it is detected that the heart rate fluctuation of the user during running exceeds the threshold value, normal physiological response instead of abnormity can be judged in combination with the movement label; the probability that normal physiological parameter fluctuation caused by movement is mistakenly marked as abnormal can be effectively reduced, and meanwhile, the pertinence of anomaly detection is improved.

The invention relates to the technical field of medical monitoring, in particular to an intelligent old people health monitoring system, which comprises a heart rate module for collecting heart rate signals, identifying local peak values in the signals to detect heartbeat, measuring time intervals between continuous peak values to determine heart beat intervals, and calculating differences between adjacent intervals to evaluate variability. According to the method, through synchronous analysis of multi-dimensional data of the comprehensive heart rate, the skin conductance and the facial expression, the comprehensive understanding and evaluation ability of the health state of the old people is enhanced. The complex relationship between the emotion change and the physiological response is accurately captured and analyzed by integrating multi-source data without singly depending on any physiological index. Through the method, the health warning signal can be identified in the subtle change, and early warning can be carried out in time. Besides, environmental factors such as illumination, music and fragrance can be dynamically adjusted according to the mood and health state monitored in real time, so that more personalized and optimized environmental response is provided.

The invention discloses an office chair cushion temperature and humidity multi-stage regulation and control method and system. The method comprises the steps that the contact state of a cushion and a human body contact interface, the local environment, human body physiological response and external environment multi-dimensional parameters are collected in real time; the parameters are matched with a dynamic reference model constructed by multi-user historical comfort data, the matching degree is calculated, and multi-level discomfort levels of all contact areas of the cushion are divided; in combination with the discomfort level and the environmental condition, generating a personalized strategy corresponding to the multi-level regulation intensity through a multi-objective optimization algorithm; and the temperature and humidity adjusting device is driven to execute multi-stage cooperative regulation according to a strategy, and feedback data is collected to update the model. The system integrates a multi-parameter acquisition module, a data processing module, an execution regulation module and the like, and can realize automatic damp-proof management of the seat cushion after the seat is separated from the seat. The problems that existing regulation and control are single, the dynamic comfort requirement cannot be met, and the hidden danger of moisture after the cushion is separated from the seat is solved, and the comfort, sanitation and durability of the cushion are remarkably improved through full-period and multi-stage precise regulation and control.

The invention discloses a physiotherapy instrument control system and method based on artificial intelligence, and relates to the technical field of intelligent medical treatment, and the method comprises the steps: collecting an electromyographic signal in real time, carrying out band-pass filtering and TK energy operator processing, and outputting a muscle activation feature vector; based on the muscle activation feature vectors, spatial-temporal features are extracted through a convolutional neural network, and a physiotherapy parameter combination is constructed; a PID controller is adopted to adjust the physical therapy parameter combination in real time, and optimized physical therapy parameters are output; performing electromagnetic thermal coupling simulation on the optimized physiotherapy parameters through finite element analysis to obtain a physiotherapy instrument control instruction; and updating the weight of the convolutional neural network by adopting a stochastic gradient descent algorithm according to the physiotherapy efficiency evaluation report, and outputting an optimization execution instruction. PID parameters are optimized through a quantum annealing algorithm, stimulation parameters are dynamically adjusted in combination with myoelectricity beta wave band phase locking, and treatment parameters and physiological response are synchronized.

The invention relates to the technical field of automobile seats, in particular to an automobile seat system and method for intelligently adjusting and relieving the back pushing feeling, and the system comprises a sensor unit which comprises an acceleration sensor, a pressure sensor and a gyroscope which are arranged on a seat and is used for capturing the dynamic change of a vehicle during acceleration and the body posture of a passenger; the heart rate monitoring sensor is arranged on the seat and used for measuring physiological indexes of a passenger and evaluating the physiological reaction of the passenger to the back pushing feeling; the dynamic supporting and adjusting unit comprises a seat adjusting assembly and air bags located at the bottom of the seat and at the backrest part; the controller unit is used for calculating and adjusting the state of the seat adjusting assembly and the inflation amount in the air bag according to data monitored by the sensor unit so as to resist back pushing feeling and relieve discomfort of passengers; the dynamic state of the vehicle is monitored through the acceleration sensor, the acceleration trend is analyzed and predicted in combination with an algorithm, the seat is adjusted in real time through active response, and discomfort brought to passengers due to sudden acceleration or deceleration is reduced to the maximum extent.

A method for performing artificial intelligence (AI) alignment on a generative AI model (GAIM), the method includes receiving a content item, which is generated by the GAIM. A computerized brain model, which has been trained to simulate responses of at least one human to content items generated by the GAIM, is applied to the content item. The AI alignment is performed on the GAIM based on a simulated response of the computerized brain model to the content item.

The invention relates to the technical field of occupational health monitoring and safety early warning, and discloses a plateau mining employee health risk early warning method based on multi-modal data, and the method comprises the steps: firstly collecting the physiological, movement and environmental data of mining employees, carrying out the time-space alignment processing, and constructing an effective hypoxia work index; secondly, extracting dual-channel physiological response characteristics representing a force-electricity and force-chemical coupling mechanism, and mapping the dual-channel physiological response characteristics to a two-dimensional state space to generate a hysteresis loop; then calculating a centroid drift vector and a coupling coherence coefficient of a hysteresis loop relative to a resting reference state, and constructing a comprehensive health risk index; and finally, executing graded early warning based on a comparison result of the index and a preset safety threshold and a coupling state. According to the method, by quantifying the dynamic response of the physiological system to physical work of the low-oxygen environment and the collaborative state between the systems, high-load fatigue and compensation function failure are effectively distinguished, and the accuracy of plateau operation early warning is improved.

The invention relates to the technical field of medical data, and discloses a postoperative rehabilitation progress intelligent evaluation method and system.According to the postoperative rehabilitation progress intelligent evaluation method and system, medical record data and postoperative rehabilitation data of all patients are obtained through a multi-dimensional management module and classified to form a patient data set and a progress data set; the intelligent evaluation module analyzes the operation difficulty of each patient in the treatment process and the postoperative rehabilitation state of the patient according to the patient data set and the progress data set, generates a corresponding difficulty coefficient and a corresponding reaction coefficient, quantifies the operation risk and the physiological response of the patient to the operation treatment scheme, pays attention to the individual difference, and improves the treatment efficiency. The intelligent evaluation module analyzes the change trend of postoperative rehabilitation data of each patient and generates a corresponding trend data set, the dynamic analysis precision is high, the health condition, the postoperative rehabilitation state and the postoperative rehabilitation progress of the patient are evaluated, corresponding rehabilitation suggestions are output, progress feedback is visualized, and the personalized rehabilitation management treatment effect is good.

The invention provides a control method and system for interaction between emergency simulation training and a real respirator, and the method comprises the steps: collecting control parameters of the respirator, and carrying out the preprocessing of the control parameters, and obtaining an equipment parameter vector; calculating a physiological response state based on the device parameter vector; the physiological response state comprises alveolar pressure and oxygenation estimation; based on the physiological response state, performing quantitative judgment on the disease stage of the patient to obtain a current disease stage, and executing a corresponding evolution instruction set; a medical specification operation reference table is constructed, a target interval is extracted from the current illness state stage and the evolution instruction set, the matching degree of the target interval and a reference interval is calculated, and the reference interval is extracted from the medical specification operation reference table; determining whether to continue evolution, enter relieving or mark training is completed based on the matching degree; the breathing gas of the patient is simulated and restored through the gas compressor and the gas mixing device and is conveyed to the real breathing machine.

The invention belongs to the technical field of lung rehabilitation training, and particularly relates to a lung rehabilitation training effect evaluation system and method based on multi-modal data fusion. According to the method, a dynamic reference model conforming to individual differences is established through three-dimensional pulmonary respiration mobility modeling based on patient CT images, individualized comparative analysis of lung function recovery states of different patients is achieved, and meanwhile external respiration dynamics and internal physiological state parameters are collected and fused; rehabilitation quality is evaluated from the two aspects of exercise performance and physiological response, scientificity and reliability of evaluation are remarkably improved, a patient can visually perceive difference between own breathing actions and an ideal state through AR visual correction prompts, active correction of actions and muscle memory formation are promoted, effectiveness of rehabilitation training is improved, and the rehabilitation training effect is improved. The training difficulty and the resistance threshold value are dynamically adjusted according to the historical evaluation result and the real-time correction effect, it is guaranteed that rehabilitation training is gradually strengthened within the safe and reasonable range, and the rehabilitation efficiency is improved.

The invention relates to the technical field of medical monitoring, in particular to an off-bed activity multi-mode monitoring risk early warning method and system. According to the method, data such as bed surface pressure, non-contact posture / displacement and vital signs are collected, time alignment and modal confidence evaluation are carried out, cross-modal consistency is calculated and gated fusion is carried out, and a risk score is obtained by combining off-bed urgency degree prediction, postural intolerance physiological response and pipeline traction risk. And outputting a prompt / early warning / alarm and adaptively updating a threshold value and parameters under nursing feedback, thereby reducing false alarm and missing alarm and realizing advanced intervention.

The utility model discloses an intelligent acupuncture needle integrated with thermal image monitoring, and relates to the field of medical equipment, in particular to the intelligent acupuncture needle integrated with the thermal image monitoring, which comprises a needle handle, a needle tip, a monitoring camera and the like. The intelligent acupuncture needle integrates modern science and technology, real-time physiological reaction monitoring of a treatment area is achieved through the monitoring camera, and the intelligent acupuncture needle has common shooting and thermal imaging functions. Thermal imaging can detect changes of local blood flow and tissue activity, a common camera records reactions such as skin color and swelling, and real-time data help an acupuncturist to accurately adjust a treatment strategy. The pressure sensor arranged in the needle head can accurately measure pressure and depth applied by acupuncture, real-time data are transmitted wirelessly, and safe and effective treatment is guaranteed. In addition, the built-in resistance wire generates heat through battery power supply, the temperature is adjustable, wireless charging is achieved through cooperation with the microwave receiver, the continuous heating function is provided, the curative effect is enhanced, and meanwhile the comfort level of a patient is improved.

The invention relates to the technical field of remote monitoring, in particular to a chronic respiratory disease patient remote monitoring system based on the Internet of Things, which comprises a physiological baseline initialization module, an event response delay measurement and calculation module, a cardiopulmonary coupling phase quantization module and a decompensation risk early warning module. According to the method, an individual blood oxygen and cardiopulmonary coupling health baseline is established to provide accurate reference for subsequent analysis, then the blood oxygen recovery time after apnea is measured and calculated, the physiological response delay characteristic of an individual is quantified, and the characteristic is used for setting a dynamic analysis window to continuously calculate the phase difference between a breathing mode and a blood oxygen signal, so that the phase difference between the breathing mode and the blood oxygen signal is calculated. By continuously comparing the current phase difference with the individual health baseline and triggering early warning when the difference value continuously exceeds a specific range, the early sign of the instability of the cardiopulmonary system can be effectively captured, the conversion from passive response type alarm to active predictive early warning is realized, and a precious time window is provided for preventing decompensation.

A microneedle array system with heterogeneous needles, designed for the enhanced transdermal delivery of bioactive agents for therapeutic and diagnostic purposes. This system includes a variety of microneedle 140 configurations, such as primary and secondary microneedles that differ in size, shape, and material to optimize delivery and functionality. Secondary needles are specifically designed with additional features such as sensors, specialized coatings, and microelectronics to perform tasks beyond simple delivery, such as in-situ detection and measurement of physiological responses, and stimulation for enhanced drug absorption and therapeutic effect.

The invention belongs to the technical field of electromagnetic stimulation treatment, and discloses an electromagnetic personalized treatment parameter generation method and system, and the method comprises the steps: obtaining a multi-source physiological signal of a patient in an electromagnetic stimulation treatment process, obtaining the personal information and medical history information of the patient, carrying out the preprocessing of the multi-source physiological signal, and carrying out the processing of the multi-source physiological signal; extracting time-domain features, frequency-domain features and nonlinear features, combining the time-domain features, the frequency-domain features and the nonlinear features with personal information and medical history information of the patient to form a physiological response feature vector, inputting the physiological response feature vector into a preset physiological response evaluation model, and calculating to obtain a current physiological state evaluation result of the patient. Inputting the current physiological state evaluation result and the current treatment stage information of the patient into a preset parameter adjustment model to generate an electromagnetic parameter adjustment scheme; through the treatment strategy chain selected based on the data information of the to-be-migrated data and the treatment demand information, data treatment is carried out while data migration is carried out on the to-be-migrated data, and the treatment efficiency during data migration is improved.

The invention discloses a shoulder operation rapid rehabilitation regulation and control system combined with an analgesia path, and the system firstly collects signals in real time through a multi-mode physiological sensing network, constructs a shoulder dynamic function spectrogram reflecting pain and functional states, and recognizes a functional abnormality core region; then, a targeted drug infusion system is controlled, and a personalized analgesia path matched with the physiological response of the object is generated in combination with a multi-physics field coupling model and a model prediction control algorithm; thirdly, calculating the comprehensive rehabilitation confidence coefficient for quantifying the rehabilitation potential by analyzing the space-time correlation between the functional spectrogram and the analgesia path; and finally, based on the comprehensive rehabilitation confidence, generating a safe, effective and object-tolerant personalized rehabilitation training instruction set by using a multi-target rehabilitation optimization model, and driving rehabilitation equipment to execute. The method has the following advantages and effects: precise space-time matching and dynamic coordination of analgesia and rehabilitation training are realized, so that the rehabilitation efficiency and quality are remarkably improved on the premise of ensuring safety.

The invention relates to the field of medical care informatics, and discloses an exercise training management system based on multi-sensor fusion, which is characterized in that the system acquires calibration data to establish an individualized exercise physiological response baseline model, inputs actual exercise performance into the baseline model in training, and determines expected physiological signs; calculating a time sequence deviation value between the expected physiological sign and the actual physiological sign; when it is monitored that the athletic performance declines, attribution is carried out based on a time sequence deviation value, and the athletic performance declines are judged to be derived from conventional fatigue or potential physiological health risks, by introducing a time sequence deviation attribution mechanism, the technical problem that in the prior art, due to data isolation, the athletic performance decline causes cannot be judged is solved, and the probability that the athletic performance declines is lowered is lowered. Therefore, the method has the capability of distinguishing conventional fatigue from potential health risks, and decision conflicts between invalid exercise guidance and health risk early warning are avoided.

An ear-worn device may include an accelerometer and / or an electroencephalography (EEG) sensor to provide recommendations based on user activity and / or physiological responses. The ear-worn device may use the accelerometer to capture acceleration data to assess the wearer's movement rate, and detect changes. Using data from the EEG sensor, the processor may detect eyelid blinks and other signals of fatigue. The processor may generate a treatment recommendation based on any combination of the movement rate, changes, eyelid blinks, and / or signals of fatigue.

This invention discloses a multimodal acupoint targeted stimulation and feedback rehabilitation device. The device integrates focused ultrasound, transcutaneous electrical stimulation, and thermotherapy modules to form a composite stimulation unit. It monitors the physiological response of acupoints in real time using bioimpedance spectroscopy and PPG optical sensors, and calculates the "Deqi Index" (DI) based on a weighted fusion of normalized impedance decrease rate and blood flow increase rate. It combines RGB-D visual dynamic tracking of acupoint coordinates and provides location confirmation through a wearable force feedback device. The central control unit adaptively adjusts various stimulation parameters based on the DI value, forming a closed-loop control of perception-decision-execution. This invention solves the problems of existing devices having a single stimulation modality, lacking objective feedback, and inaccurate positioning, significantly improving the accuracy, effectiveness, and intelligence level of acupoint rehabilitation therapy.

The invention belongs to the technical field of ischemia pre-adaptation training instruments, and particularly relates to an ischemia pre-adaptation training method and system based on blood pressure value feedback. Calculating training control parameters based on the physiological response model, and performing real-time risk judgment by using the risk prediction model; controlling the pressure of the pressurizing cuff according to the control parameters; the physiological response model stores training data and continuously optimizes the model. The system is an integrated device for implementing the method. A training process based on a personalized trainer and a learning process of a reinforcement learning algorithm are fused to realize man-machine interaction, so that the problem of control model stiffness caused by an existing pressure control strategy based on a static formula, a fixed coefficient or a learning model with relatively weak personalization is solved; according to the method, the problems of process lack of individual adaptive ability, control model stiffness, security mechanism lag and the like are solved, and safe and personalized intelligent closed-loop training with sustainable evolution ability is realized.

The application relates to the technical field of medical care information science, and discloses an old-age health prediction method and system, which comprises an information collection module, a phase-locked analysis module and a trend determination module, the information collection module synchronously acquires a behavior perturbation sequence and a physiological response sequence; the phase-locked analysis module calculates dynamic phase offset characteristics between the behavior perturbation sequence and the physiological response sequence, and determines a logical deviation residual of a measured phase offset relative to a reference mapping track by using a logic transfer check unit; and the trend determination module monitors a second-order cumulative change rate of the logical deviation residual in a sliding window, and outputs a warning signal when the second-order cumulative change rate exceeds a stability threshold value; the application can perceive the deterioration of body feedback regulation flexibility before a physiological parameter appears abnormal, and avoids prediction failure caused by a physiological compensation mechanism of an old individual by quantifying the information transmission efficiency of a feedback loop.

The application belongs to the technical field of dysphagia rehabilitation, and particularly relates to a cold stimulation device for dysphagia rehabilitation, which comprises a supporting column, a reciprocating electric telescopic rod coaxially and fixedly connected to one end of the supporting column, a semiconductor touch head fixedly connected to a telescopic end of the reciprocating electric telescopic rod, a biting seat fixedly connected to the supporting column, biting air bags fixedly and symmetrically connected to the biting seat, the biting air bags being communicated with the supporting column, and a detection tube fixedly connected to the biting seat. The oral cavity sealing mechanism automatically triggered by biting action can accurately detect the swallowing action according to the negative pressure of the oral cavity. After the effective swallowing action is detected, the stimulation can be paused through a delay start switch, the next round of training can be automatically started after the rest, and the timing and rhythm of each stimulation are ensured to be consistent with the physiological response. The normal exhalation can be realized while the oral cavity sealing space is formed, and the breathing safety is ensured.

This invention discloses a method and system for evaluating the effectiveness of photostimulation based on multimodal feature fusion, belonging to the field of big data analysis technology. The method and system include the following steps: S1, acquiring raw observation data and performing time axis relocation, dynamic denoising, normalization, and sliding time window segmentation; S2, evaluating the state of the stimulation process and selecting effective windows; S3, extracting neural activity response features and hemodynamic response features, and performing physiological response reliability assessment; S4, performing consistency fusion to evaluate the effectiveness of photostimulation. This invention effectively improves the stability and reliability of effectiveness evaluation during head-mounted photostimulation, solving the problems of difficulty in distinguishing between abnormal stimulation pathways and true brain tissue responses, as well as insufficient consistency of results across batches of experiments.

The invention relates to a trajectory type shock wave noninvasive acupuncture system based on manipulation parameterization, and the system comprises a user interaction terminal which is used for receiving a traditional Chinese medicine manipulation operation instruction inputted by an operator; the central processing and control unit is used for converting the traditional Chinese medicine manipulation operation instruction into a corresponding shock wave parameter set through a pre-constructed parameter mapping model; the ballistic shock wave generation module is connected with the central processing and control unit and used for generating ballistic shock waves according to the shock wave parameter set; the treatment head is connected with the ballistic shock wave generation module and used for outputting the ballistic shock waves to human body acupuncture points; the physiological signal acquisition module is used for acquiring physiological parameters of a human body acupuncture point area in real time; the central processing and control unit is further configured to adjust the shock wave output parameters according to the comparison result of the physiological parameters and a preset physiological response model. According to the application, parameterized simulation and dynamic adjustment of traditional Chinese medicine manipulation are realized through real-time physiological feedback, and the treatment accuracy is improved.

The invention provides a vehicle control method and device based on emotion recognition, equipment and a storage medium. The method comprises the following steps: forming an environment vector by monitoring environment information in a vehicle in real time, thereby quantitatively representing the comprehensive state of the environment in the vehicle; the weight parameter of the facial action unit is dynamically adjusted based on the environment vector, so that the weight of physiological reaction caused by environment discomfort in emotion recognition can be effectively reduced; the targeted parameter correction enables the finally obtained emotional state to be a more real emotional reflection after the environmental interference is removed, and the accuracy of emotion recognition is remarkably improved. On the basis, the system triggers the corresponding vehicle control operation according to the purified emotional state, the accuracy of interaction feedback is ensured, and the reliability of vehicle man-machine interaction and the user experience are improved.

Disclosed is a system, a device, and a method for neuro-acoustic vagal modulation The method includes the steps of receiving (706) a session type selection, determining 5 (708) stimulation parameters, generating (710) stimulation signals, and transmitting (712) the signals to a neuro-acoustic vagal modulation device (102) positioned behind a user's ear. The method includes receiving (714) physiological response data from the device (102) or an auxiliary wearable device (108), dynamically adjusting (716) the stimulation parameters based on the received data, and transmitting (718) the adjusted 10 signals to the device (102).

The invention discloses a heart failure rehabilitation exercise data management system and method, and relates to the technical field of heart failure rehabilitation exercise data management.The heart failure rehabilitation exercise data management method comprises the steps that historical rehabilitation data of a heart failure patient in different stages are collected, the stage normal interval of the final core feature of each stage is obtained, and the current rehabilitation stage of the patient is judged; physiological response data and motion data of a patient during rehabilitation treatment at the stage are collected in real time through wearable equipment, first, a first risk score is calculated based on the physiological response data, and then the motion data and the physiological response data are combined to obtain a motion load dynamic index; and a second risk score is calculated based on the exercise load dynamic index, and finally the first risk score and the second risk score are fused to carry out real-time early warning of rehabilitation exercise of the patient. The accuracy of heart failure rehabilitation data stage division and patient rehabilitation exercise early warning is improved.

Systems and related operating methodologies are disclosed. An exemplary operating method obtains sensor data that indicates a physiological characteristic of the user, the sensor data provided by an analyte sensor, and determines that a current level of the physiological characteristic differs from a user-specific target level by a quantifiable amount. The method continues by searching an activity correlation database to locate one or more physical activity events correlated with the quantifiable amount of the physiological characteristic. The activity correlation database is populated with event-correlated physiological responses that associate physical activity events with corresponding changes in the physiological characteristic. A recommendation is provided for the user. The recommendation specifies the one or more physical activity events.