Health-Index Calculation TRIZ Cases

A home visit assessment system generates virtual representations of living conditions to standardize caregiver data entry.

Calculates index values from multiple blood biomarkers to support cognitive impairment determination.

Processor delays alert issuance by classifying detected cardiac events and determining an offset time based on device conditions.

A non-contact surface sensor detects brain volume changes to calculate pulsatility metrics.

Linked ultrasound sensors maintain geometric distribution while a control module automatically determines fetal heart position.

Sensors detect user condition and location, enabling automatic transmission to rescuers without manual input.

A work assist apparatus acquires biological and resume data to compute health risk evaluation values for task matching.

Embedded bed sensors measure patient pressure and moisture to feed computing models that identify root causes of pressure injuries before they worsen.

Segmented LED arrays enable noninvasive total hemoglobin index screening, eliminating invasive blood draws and reducing treatment costs.

A medical information processing apparatus generates age-based health data distributions to display measurement results alongside corresponding evaluation sentences.

AI models analyze tumor images to predict genetic mutations, replacing invasive tissue sampling and reducing clinical trial costs.

Imaging subsurface tissue detects pain onset earlier than surface measurements, eliminating detection latency and sweat reabsorption delays.

A machine learning system generates personalized survival probability predictions for organ transplant recipients using pre-operative and post-operative patient datasets.

A system correlates user health knowledge with outcomes to deliver personalized services.

A system converts cardiac signals into visibility graphs to determine maturation indices for premature infants.

Merging acceleration and electrodermal activity signals into one device resolves the trade-off between assessment precision and hardware complexity.

A wearable device analyzes breath samples to generate personalized product recommendations based on individual biological markers.

A medical support system estimates induced pluripotent stem cell production probability using patient biometric data.

Acquiring orthogonal slices instead of full volumes cuts acquisition delay, maintaining target alignment during patient motion.

A recurrent neural network analyzes time-series vital measurements to classify patient risk levels and generate adjusted monitoring schedules.

Segmenting volumetric breast ultrasound data into navigable views reduces interpretation time while maintaining detection accuracy.

Deep learning analyzes cell nuclei and types in biopsy images to estimate cancer risk, addressing unreliable traditional prediction methods.

A computing system generates personalized edible ration programs using stress machine-learning models to determine physiological influences.

Workflow server segments health events into priority queues to reduce latency for critical data.

A radar-based monitoring system tracks user biometrics and screen time to promote digital well-being.

A computing system derives hybrid performance metrics by jointly processing time-aligned sensor and position data from sports equipment.

A health survey system uses pictogram answers to create user profiles.

A health management system decouples raw weight data from user feedback to prevent discouragement.

A medical image diagnostic apparatus synchronizes images with cardiac time phases to compute biological indexes and display treatment device positions.

A beat-space conversion system transforms electrocardiogram time-series data into heartbeat intervals to extract precise frequency domain features.

A medical system adjusts patient therapy using implantable and wearable electrodes.

A trained predictive model aligns unlabeled gene expression data to determine PD-L1 status.

Computer vision algorithms analyze food images to estimate nutritional intake, reducing manual data entry errors in personalized meal planning.

A symbolic analysis system transforms streaming vital signs data into discrete sequences to identify high-risk patient patterns.

A system loads patient data records and sorts them by deviation from reference values to generate a prioritized list.

A biological signal monitoring apparatus tracks physiological values across two distinct time periods to identify patient deterioration.

A biological information measurement device acquires patient data to determine risk status and issue accuracy warnings.

A drug delivery system calculates aggregate insulin-on-board amounts using saturable absorption kinetics to adjust subsequent dosing estimates.

Patient monitoring system generates event markers by comparing physiological signal metrics against reference values.

A programmable interface connects medical devices to a main platform, processing waveform data through smart sampling and feature extraction.

A computer program segments cerebral and systemic parameters into intervals to calculate evolving severity scores for immediate clinical feedback.

EEG waveform analysis extracts frequency components to generate motor control scores, replacing subjective clinical assessments with quantitative data.

A heat consumption estimation method segments motion into steady-state and recovery stages to improve accuracy.

Filters methylation profiles to isolate age-correlated CpG sites, resolving heterogeneity loss in bulk samples.

A computational method calculates pulmonary blood flow using standard physiological parameters from metabolic carts and blood gas analyzers.

A computer-implemented method estimates patient length of stay by analyzing alarms triggered by medical devices.

A sleep tracking system displays stage representations that indicate ambiguous periods containing multiple sleep stages.