相当的年代imply the most advanced PPG sensors for wearables & hearables available today
Valencell provides the technology, the team, and the expertise to make biometrics work in wearables and hearables
- Proven innovation with over 100 foundational18lickc新利 授予另外50多项专利申请
- PPG sensor system continuously measures heart rate, VO2, energy expenditure, R-R interval, signal quality and much more
- Active Signal Characterization technologyenables highly accurate biometrics in wearable devices even during vigorous activity
- PPG sensor tech integrates seamlessly into any wearable or hearable device
- 适合使用18新利登录地址和18IUCK新利官网 devices
Many people think you can create accurate biometric wearable devices by piecing together some LED’s, some firmware, some algorithms, and calling it a heart rate sensor. It’s not that simple.
Valencell has learned over many years of R&D, trial & error, and product development that the systems approach to building biometric wearable devices is most effective. Everything must be designed and developed to work together from the start – the optomechnanics, the firmware, the algorithms, and thetesting & validation processes.
- Finally, even if you get the hardware and the software working together, you have to test and validate that it works on people of all shapes, sizes, colors, genders, and fitness levels.
Valencell’s PPG sensors can be used in wearables and hearables for virtually anyone, anywhere, doing anything.
PerformTek®PPG传感器技术是唯一持18新利在线官网登录续的心率传感器技术，在几乎任何运动中和几乎任何环境中都有几乎可以准确。Read more about our testing methods here.
We’ve been18lickc新利 in optical heart rate sensor technology for over 10 years, before wearables even existed. Our PPG sensor accuracy has been proven by independent scientific validation and by users of Valencell-powered products every day.
合作Sonion, the global leader in micro acoustic and micro mechanical technologies and solutions for hearing instruments and specialty earphones,expands the boundariesfor the use of biometric sensors in the ear. In the partnership, Valencell provides the industry’s most advanced biometric sensor modules for hearables and wearables, which Sonion will optimize for size, power consumption and cost for in-ear and on-ear applications.
PPG Sensor Design
HOW VALENCELL IS DIFFERENT
Photoplethysmography (PPG) is not new. It’s been used for decades to measure blood flow changes and translate these changes to pulse rate. However, PPG sensors are extremely sensitive to motion, particularly in a wearable device, and have significant challenges measuring biometrics accurately during daily activities and exercise. Our patented PerformTek® biometric technology has solved many of these problems.
Like the traditional PPG approach, PerformTek® heart rate sensor technology measures weak blood flow signals by shining light at the skin with an optical emitter and sensing the scattered light with a photodetector. The key differences are Valencell’s patented optomechanics and signal extraction methodologies, which employ主动信号表征to actively remove optical signals associated with motion artifacts (such as skin motion and footsteps) and environmental exposure (such as sunlight) from the photodetector.
It’s like active noise cancellation for biometric wearables. The result is a clean signal that contains more accurate information about blood flow. Because blood flow modulates with heart rate and respiration rate, PerformTek-powered algorithms can accurately extract heart rate, RR-interval, respiration rate, and other blood flow parameters even during intense exercise. To gauge user activity level and to generate activity context, the PerformTek earbud sensor module leverages the accelerometer that is built in to the sensor module. The PerformTek signal extraction method applies a proprietary algorithm to the accelerometer signal to measure running, cycling and activity cadence and to estimate speed and distance traveled. Valencell also estimates VO2 and calories burned by processing both the accelerometer signal and blood flow signal.
Valencell has a dedicated team of data scientists that apply data science and machine learning techniques to every aspect of our biometric sensor technology, including:
- Demonstrating robust biometric assessments and user experiences