Inertial Sensors TRIZ Cases

See how an air-permeable capacitive sensor grid embedded in bedding wirelessly detects sleep st

See how an air-permeable capacitive sensor grid embedded in bedding detects sleep states and vi

See how segmented inflatable bladders adjust head and torso angles in response to real-time sle

See how a handheld tool uses sensors and actuators to detect unintentional muscle movements and

See how dual IMU sensors and motion generating mechanisms stabilize handheld tools for users wi

See how a folded paper chair with counterweight and accelerometer replaces mechanical adjustmen

See how an active chair uses tilt sensors to detect subtle seat lean around x and y axes, provi

See how a handheld tool with user-assistive device automatically measures food mass during eati

See how force sensors and inertial tracking in a handheld utensil automate nutrition intake mea

See how dual inertial sensors and motion-generating mechanisms stabilize handheld tools for tre

Sensors track unintentional hand motion and drive equal-opposite movement in a handheld tool to reduce tremor interference during daily tasks.

Baseline and real-time wearable data are compared to detect travel-related alertness triggers and send guidance to user devices or vehicles.

Baseline and real-time wearable data trigger alertness insights that user devices or vehicles can use for safer travel guidance.

Local biometric processing and feedback sensing reduce exposure and data loss when wearables share health data with external electronics.

Machine learning filters vehicle vibration noise from remote body-motion sensing to deliver comfortable, accurate in-car vital sign monitoring.

In-vehicle sensors flag likely passenger illness and trigger fleet cleaning or suspension to limit infectious exposure in ride sharing.

A metal-free biofuel cell powers a disposable sensor catheter, improving physiological measurement while simplifying disposal and reducing cost.

A biodegradable biofuel cell powers a disposable sensor probe, enabling accurate tract measurements with simpler handling and disposal.

Low-power motion and capacitive sensing activate high-power wearable sensors only when the device is on-body, extending battery life.

Low-power motion and position sensing wakes high-power wearable sensors only when the device is worn, extending battery life without losing responsiveness.

Real-time sleep progression data triggers lighting, sound, and scent changes to improve sleep continuity and waking conditions.

A controller disables the PPG sensor after bed entry and re-enables it at sleep onset to avoid light leakage while preserving vital-sign monitoring.

Using built-in mobile sensors and location inference, this case shows continuous user activity monitoring without dedicated wearable hardware.

Multiple body-worn motion sensors use gravity-based alignment and signal subtraction to remove passive motion and improve energy expenditure estimates.

Separating rotational respiration signals from linear motion lets a bolus sensor measure livestock heart rate continuously with less stress.

Adjustable electrodes and image-guided placement cut EEG setup time while preserving signal quality across varied head shapes.

Single-site PPG amplitude and morphology analysis plus fall and wearing detection helps identify cardiac arrest early and trigger faster alerts.

IMU motion features and selective user-confirmed labels improve movement classification accuracy for passive health and treatment monitoring.

Pressure sensors placed at medial and lateral foot zones reveal shoe pressure points for more accurate fit assessment and comfort feedback.

Continuous corneo-retinal and head-motion sensing improves nystagmus detection outside the clinic while reducing bulky equipment and manual review.

An accelerometer bolus tracks rumen contractions and eructation events to estimate ruminant methane emissions in real time with less sensing complexity.

A mixed ADC-DAC digital filter cuts drift, noise, and saturation in ballistocardiography signals for stable cardio-respiratory monitoring.

Multiple emitters and detectors at different radial distances help wrist pulse oximetry correct bias, detect poor placement, and resist motion artifacts.

Objective pain assessment combines optical, electrical, and temperature sensing with cerebral hemodynamic tracking for real-time management.

Millimeter-wave radar, proximity sensing, and IMU fusion enable contactless chest-aligned vital sign tracking with less motion noise.

Chest accelerometer signal intervals are reconstructed by autoencoders trained on healthy subjects to flag heart failure more reliably than amplitude measures.

Warning limits adapt to fatigue, exercise content, goal progress, and athletic ability to reduce unnecessary alerts during training.

A rechargeable implantable ECG platform adds configurable sensors and data offloading to extend monitoring without reimplantation.

Beat-to-beat PPG analysis separates AC waveform changes and DC baseline trends to noninvasively detect volemic status and vascular tone.

Accelerometer-based seismocardiography extracts systolic and diastolic periods without microphone noise, enabling portable early cardiopathy detection.

Continuous subcutaneous ECG and EEG sensing with machine learning improves mental state assessment when self-reporting and wearables fall short.

Respiration and ECG pattern comparison detects 180-degree implant rotation quickly, improving orientation accuracy while limiting power use.

Motion data from a wearable triggers section-by-section exercise content on a mobile display, avoiding manual switching during workouts.

By checking gravity and walking acceleration patterns, this case verifies waist sensor alignment before gait analysis for more reliable posture feedback.

Motion-based activity sensing adjusts heart rate thresholds to capture relevant arrhythmia episodes while reducing false triggers and power use.

Electret helmet sensors track pressure and acceleration, then alert staff when single or cumulative impacts exceed injury thresholds.

By comparing estimated joint acceleration with sensor data, this case improves movement recognition and catches incorrect wearable sensor placement.

Activity and physiological signals are combined to tailor alert intensity, improving response to abnormal vital signs without unnecessary disturbance.

A single foot sensor detects gait events and feeds a constrained geometric model to estimate lower limb motion without multiple leg sensors.

Gait events from one foot sensor anchor a constrained geometric model that tracks lower limbs without multiple leg sensors or premeasured lengths.

Temperature-aware compensation adjusts glucose sensor sensitivity and delay effects to improve reading accuracy and insulin dosing precision.

Local principal-component processing of EMG and motion signals enables long-term Parkinson's monitoring with lower wireless data load and power use.

Body water trend analysis and weighted user context enable personalized dehydration thresholds with fewer false alarms.

High-density EMG arrays correlate agonist and antagonist motor unit spike trains to detect pre-motor tremor signals before visible Parkinsonian symptoms appear.

A handheld sensor device pairs with a smartphone to enable accurate self-administered grip, fatigue, and health condition testing outside the lab.

A single chest patch combines PPG, ECG, and SCG sensing with viscoelastic strain isolation for more reliable home sleep disorder monitoring.

Head-motion chaos analysis from a cranial accelerometer helps detect LVO before hospital imaging, improving triage speed and accuracy.

By distinguishing true wake-up intent from brief stirring, the wearable avoids redundant sleep analysis and delivers results faster.

A silicon-cap photodiode and MEMS accelerometer share one package to synchronize optical and motion data, improving PPG accuracy with lower power.

A removable multi-mode cardiac sensor switches between patch and holster wear to maintain arrhythmia monitoring without implants or long-term patch discomfort.

Motion and orientation sensors infer respiration during sleep to screen apnea and hypopnea events without invasive multi-sensor studies.

Corrects earbud accelerometer misalignment with orientation calibration and axis fusion to improve BCG signal quality and biomarker estimates.

An inertial sensor and fingertip load setup captures slight index finger contractions while limiting muscle compensation for objective nerve recovery assessment.

A fall detection algorithm computes velocities and displacements from time-varying accelerations to identify movement patterns.

Apparatus determines user-specific activity intensity using kinematic data and a server-derived calibration metric.

A handheld computer engages the vestibular system through rotation to detect cerebral function reductions.