Capture specified high‑quality data with precision vision algorithms
Acquire large volumes of long‑term, human‑related process data required in medical and research workflows
Long‑term changes in joint mobility and movement behavior often reflect trends earlier than clinical symptoms. Continuous observation during rehabilitation and exercise has significant value for data collection in neurology, orthopedics, and child development.
Rehabilitation process data is often missing, and home rehabilitation lacks effective data monitoring
Medical research requires not only massive long‑term process data but also faces subjective bias in physician assessments, and patient status is difficult to quantify through self‑reported feedback alone.
Continuity, precision, and quantifiability
Manual recording is inefficient and prone to omissions; observer bias causes data skew; questionnaire and interview data lack continuity and are influenced by personal expression and recall, making quantification difficult; single assessments cannot capture long‑term dynamic changes.
Healthcare and medical research industries are centered on "people"
Conclusion: Human behavior is difficult to record continuously, objectively, and in a standardized way
Precise acquisition of continuous behavioral data, recording and correcting patient rehabilitation movement data
Lite SeriesLightweight devices
Pro SeriesHigh‑performance series
How to choose equipment for collecting and analyzing data?
Xeroptix offers multiple hardware options
Lite Series
Lightweight, customizable devices
Pro Series
High performance
Including Xeroptix Aurora Arc Gen 1, 2, and 3
What is the completion rate of a patient's rehabilitation training?
What is the joint flexibility (maximum angle / completion count) for the shoulder, elbow, and wrist?
What is the current walking speed of an elderly person? Is the gait normal?
Left‑right comparison data for arms and legs of rehabilitation subjects
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Automatically record completion quality, joint range of motion, and strength changes for each rehabilitation session, providing objective data for physicians to adjust rehabilitation plans
Joint flexibility data is valuable in neurodegenerative disease research—for early screening, condition assessment, recovery evaluation, and more
Motion planning, slowness, and coordination for early behavioral anomaly assessment in Alzheimer's disease
Left‑right motion imbalance is valuable in orthopedic rehabilitation and early‑stage recovery
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Monitor heart rate, blood pressure, and sleep data
Use IMU and pressure sensors to simulate gripping, extension, and other motions to support hand function and skeletal recovery
Design programs based on subject characteristics using rehabilitation and exercise science expertise
Combine Xeroptix with vital signs data for more comprehensive, science‑based assessment of patient rehabilitation status and data completeness
Overcome one‑to‑one scenario limits of traditional rehabilitation devices; collect more than a single data type and support diverse rehabilitation processes and research
Record training process data from rehabilitation programs, then intelligently update program content with data‑driven insights to support and validate program design
Support customized training content, encourage self‑directed rehabilitation, and provide real‑time correction alerts without relying on staff
Angle, speed, count, direction, motion assessment, and more
99.9% recognition accuracy
Xeroptix provides rich industry algorithm templates with precise recognition results, meeting diverse data collection and rehabilitation monitoring requirements in healthcare.
Edge computing with cloud collaboration
Improved satisfaction
The Xeroptix solution visualizes rehabilitation assessment data to improve customer satisfaction; edge computing protects privacy with all images processed locally and anonymized before upload, meeting healthcare privacy requirements.
Process data recording
Scientific research support
Xeroptix precisely identifies and records critical process data through algorithms, supporting scientific research such as subsequent disease risk assessment.
