Metal Industries Research & Development Centre

Sheng-Hong Yang

Bo-Wei Pan

Jian Jia Zeng

Jian-Jia Zeng

Jian-Jia Tzeng

Tzyy-Ker Sue

Kai-Szu Lo

Ping-Yi Hsieh

A surgical robotic arm control system and a control method thereof are provided. The surgical robotic arm control system includes a surgical robotic arm, an image capturing unit, and a processor. The surgical robotic arm has multiple joint axes. The image capturing unit obtains a first image. The processor executes a spatial environment recognition module to generate a first environment information image, a first direction information image, and a first depth information image according to the first image. The processor executes a spatial environment image processing module to calculate path information according to the first environment information image, the first direction information image, and the first depth information image. The processor executes a robotic arm motion feedback module to operate the surgical robotic arm to move according to the path information.

Surgical robotic arm control system and control method thereof

A surgical robotic arm control system and a surgical robotic arm control method are provided. The surgical robotic arm control system includes a surgical robotic arm, a first image capturing unit, a second image capturing unit, and a processor. The first image capturing unit is used for obtaining a field image. The field image includes a first target image of a target object. The second image capturing unit is disposed at an end position of the surgical robotic arm and is used to obtain a second target image of the target object. The processor analyzes the field image to obtain robotic arm movement information, and controls the surgical robotic arm to move to approach the target object. The processor analyzes the target image to obtain robotic arm rotation information, and controls an angle and a posture of the surgical robotic arm.

Surgical robotic arm control system and surgical robotic arm control method

An automatic control method of a mechanical arm and an automatic control system are provided. The automatic control method includes the following steps: obtaining a color image and depth information corresponding to the color image through a depth camera; performing image space cutting processing and image rotation processing according to the color image and the depth information to generate a plurality of depth images; inputting the depth images into an environmental image recognition module such that the environmental image recognition module outputs a displacement coordinate parameter; and outputting the displacement coordinate parameter to a mechanical arm control module such that the mechanical arm control module controls the mechanical arm to move according to the displacement coordinate parameter.

Automatic control method of mechanical arm and automatic control system

A method for measuring spasticity is provided and includes: obtaining sensing signals corresponding to a limb movement through at least one sensor during a period of time; transforming the sensing signals into a two-dimensional image; and inputting the two-dimensional image into a convolutional neural network to output a spasticity determination result.

Method and system for measuring spasticity

An elbow joint rehabilitation system and an elbow joint rehabilitation method are provided. The elbow joint rehabilitation system includes a support member, a motor, a torque sensing unit, a first electromyography sensor, a second electromyography sensor and a motor control device. In the elbow joint rehabilitation method, the support member is configured to support an arm of a patient. Thereafter, the torque sensing unit is configured to sense the torque applied on the support member to obtain a sensed arm torque signal. Then, the first electromyography sensor and the second electromyography sensor are configured to sense the muscle activities of biceps and triceps of the patient to obtain electromyography signals. Thereafter, the motor is controlled to drive the support member to perform rehabilitation in accordance with the sensed arm torque signal, the electromyography signals and a current support member position provided by the motor.

Elbow joint rehabilitation system and elbow joint rehabilitation method

A medical image modeling system and a medical image modeling method are provided. The medical image modeling system includes an input device, a processing device, and a storage device. The input device obtains medical image data. The processing device is coupled to the input device. The processing device converts the medical image data into a bone model in response to a first operational command. The storage device is coupled to the processing device. The storage device stores a model database. The processing device reads the model database in response to a second operational command to obtain a bone reconstruction block corresponding to a defect block of the bone model. The processing device integrates a bone reconstruction model depicted corresponding to the bone reconstruction block into the defect block of the bone model to generate an integrated bone model.

Medical image modeling system and medical image modeling method

An image analyzing method is provided and includes: extracting a first feature vector according to global information of a digital image; dividing the digital image into multiple regions, and inputting each region into a convolutional neural network to obtain a second feature vector; merging the first feature vector with the second feature vectors to obtain a third feature vector; and performing an image analyzing process according to the third feature vector.

Growing community of inventors

Kaohsiung, Taiwan

Sheng-Hong Yang