BEIJING, Sept. 8,
2023 /PRNewswire/ -- MicroCloud Hologram Inc.
(NASDAQ: HOLO) ("HOLO" or the "Company"), a Hologram Digital Twins
Technology provider, today announced the launch of a
multi-layer joint learning framework based on logistic regression
models to construct a motion training system based on machine
learning and SVM holographic brain-computer interface.
Brain-computer interface is a communication technology that does
not depend on people's normal peripheral nerves and muscle tissue.
It is a direct connection pathway established between human or
animal brain (or culture of brain cells) and external devices. The
motion training system of holographic brain-computer interface
solves the difficult problem of exercise for patients with
functional disorders, and stimulates, extracts and utilizes their
active movement willingness. And strengthen the use of the affected
limb, improve the motor function of the limb. By combining MEMS
flexible microsensor array technology with BCI brain-computer
interface technology, multi-source information fusion and adaptive
feedback control technology, it can not only significantly improve
the motor function of limbs, but also promote the reorganization of
the functional dependent area of the cortex, thereby expanding the
cortical motor control area of the affected limb, providing an
effective tool for early rehabilitation training of patients with
hand dysfunction.
HOLO also built a brain-computer interface experimental control
platform based on holographic AR, which uses the holographic naked
eye image as a visual stimulator to induce EEG signals, so that
users do not need to perform visual stimulation in a fixed
position, which can enhance the applicability in complex
environments, so as to achieve more natural human-computer
interaction. Then the A/D sampling of the EEG signal is controlled
by the motion training system of the holographic brain computer
interface through digital signal processing, and the A/D sampling
of the digital EEG signal is sent to the DSP for holographic
digital filtering. The filtered EEG signal is then identified and
matched by intelligent algorithm according to holographic data in
holographic data tag library. Finally, the EEG holographic data is
displayed and saved by complex algorithm and parallel
communication.
The holographic brain-computer interface motion training system
based on machine learning and SVM is composed of signal
acquisition, feature extraction, feature classification and
external control equipment:
Signal acquisition: The brain computer interface collects
signals of neuronal activity through microelectrodes implanted in
the cerebral cortex;
Feature extraction: The collected signals are decoded, then
encoded, and converted into machine-readable instruction signals.
Common methods include fast Fourier transform (FFT), discrete
Fourier transform (DFT), wavelet transform (WT), independent
component analysis (ICA), common spatial mode (CSP) and some
improved methods based on the above methods.
Feature classification: The extracted feature signals are
further classified. Commonly used classifiers include linear
classifiers, support vector machines (SVM), neural networks and a
combination of various classifiers.
External control device: The control process in the form of
signals to the brain feedback to achieve human-computer
interaction.
In the field of rehabilitation medicine, the motion training
system of holographic brain-computer interface can effectively
assist the rehabilitation training of neuromuscular patients such
as stroke or spinal cord injury by controlling robotic arms and
exoskeleton robots. With the continuous exploration of brain
structure and function by modern medicine, human beings have more
in-depth research on brain functional areas such as vision,
hearing, movement and language. Micro-cloud holographic obtains
information of these brain functional areas through brain-computer
interface equipment and analyzes it, and lays out the diagnosis,
screening, monitoring, treatment and rehabilitation of neurological
and psychiatric diseases. We are also exploring potential future
research and application directions.
About MicroCloud Hologram Inc.
MicroCloud Hologram Inc. (NASDAQ:HOLO) engages in the research
and development, and application of holographic technology.
MicroCloud Hologram provides its holographic technology services to
its customers worldwide. MicroCloud Hologram also provides
holographic digital twin technology services and has a proprietary
holographic digital twin technology resource library. MicroCloud
holographic digital twin technology resource library captures
shapes and objects in 3D holographic form by utilizing a
combination of holographic digital twin software, digital content,
spatial data-driven data science, holographic digital cloud
algorithm, and holographic 3D capture technology. MicroCloud
Hologram technology services include holographic light detection
and ranging (LiDAR) solutions based on holographic technology,
holographic LiDAR point cloud algorithms architecture design,
technical holographic imaging solutions, holographic LiDAR sensor
chip design, and holographic vehicle intelligent vision technology
to service customers that provide holographic advanced driver
assistance systems (ADAS).
Safe Harbor Statements
This press release contains "forward-looking statements" within
the meaning of the Private Securities Litigation Reform Act of
1995. These forward-looking statements can be identified by
terminology such as "will," "expects," "anticipates," "future,"
"intends," "plans," "believes," "estimates" and similar statements.
Statements that are not historical facts, including statements
about the Company's beliefs and expectations, are forward-looking
statements. Among other things, the business outlook and quotations
from management in this press release, as well as the Company's
strategic and operational plans, contain forward−looking
statements. The Company may also make written or oral
forward−looking statements in its periodic reports to the U.S.
Securities and Exchange Commission ("SEC") on Forms 20−F and 6−K,
in its annual report to shareholders, in press releases and other
written materials and in oral statements made by its officers,
directors or employees to third parties. Forward-looking statements
involve inherent risks and uncertainties. A number of factors could
cause actual results to differ materially from those contained in
any forward−looking statement, including but not limited to the
following: the Company's goals and strategies; the Company's future
business development, financial condition and results of
operations; the expected growth of the AR holographic industry; and
the Company's expectations regarding demand for and market
acceptance of its products and services. Further information
regarding these and other risks is included in the Company's annual
report on Form 20-F and current report on Form 6-K and other
documents filed with the SEC. All information provided in this
press release is as of the date of this press release, and the
Company does not undertake any obligation to update any
forward-looking statement, except as required under applicable
laws.
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SOURCE MicroCloud Hologram Inc.