Industrial Technology Research Institute

Ho-Hsin Lee

Yue-Min Jiang

Jian-Ren Chen

Yi-Fei Luo

Min-Yi Hsieh

Chih-Jen Hsu

Leii H Chang

Szu-Han Tzao

Chii-Yah Yuan

Su-Chen Huang

Jian-Hong Liu

Ren-Guey Lee

Cheng-Li Chang

Duan-Yu Chen

Chun-Fu Yeh

Shang-Chih Hung

I-Ju Yeh

Wei-Chieh Lin

Li-Ying Wu

Tsai-Ya Lai

A portable medical device includes a portable medical bag, a plurality of connectors and a processor. These connectors respectively connect the portable medical bag and every medical device contained inside the portable medical bag. The portable medical bag obtains the device management information of each the medical device through these connectors. The device management information includes the remaining power of medical device. The processor calculates the charge strategy information of the corresponding medical device according to the medical device information, address information and device management information. In addition, a management method for portable medical device is also provided.

Portable medical device and management method thereof

A wound multiple sensing method, including: calculating the similarity between the current data sequence and each of the case-data sequences in each of the reference cases; selecting the case-data sequence which has the greatest similarity with the current data sequence, from the case-data sequences in each of the reference cases, to be a similar case-data sequence in each of the reference cases, wherein each similar case-data sequence corresponds to a similar case treatment; performing a multiple regression analysis using the similar case-data sequences and the similar case treatments to calculate a fitness function, wherein the dependent variable of the fitness function is a wound change; performing a parameter optimization algorithm using the current data sequence and the fitness function to calculate an optimal treatment which maximizes the wound change, and to calculate an expected wound change value that corresponds to the optimal treatment.

Wound multiple sensing method and wound multiple sensing system

A lung sound monitoring device is provided. The lung sound monitoring device includes an acoustic sensor and a processor. The acoustic sensor is configured to capture the chest cavity sound of a subject at a first monitoring position on the subject and convert the chest cavity sound into a first chest cavity sound signal. The processor is configured to receive the first chest cavity sound signal and perform a filter process to obtain a first lung sound signal, and convert the first lung sound signal into a first lung sound spectrum using time-domain frequency-domain conversion. The processor acquires a first intensity index according to the first lung sound spectrum, and outputs a prompt signal according to the first intensity index to indicate whether the first monitoring position is a qualified monitoring position.

Lung sound monitoring device and lung sound monitoring method thereof

A system for analyzing wound status is provided. The system includes an image obtaining device and an image analyzing device. The image obtaining device is configured to obtain a plurality of infrared (IR) images which are photographed from a wound of a user's body portion, wherein the plurality of IR images are photographed at different time. The image analyzing device is configured to align the plurality of IR images based on features of non-wound regions from the plurality of IR images, and then analyze wound image regions from the plurality of IR images for finding out variations of the wound.

Method and system for analyzing wound status

A system for object recognition includes an image/spectrum sensing device, to fetch an object image from a real object and sense spectra at sensing regions of the real object. A fetching module obtains a real-object image feature pattern for each ROI of the object image. An analyzing module for object image feature searches for a first candidate object from data bank and analyzes a correlation between the real object and candidate object. A fetching module for object spectrum feature obtains a real-object spectrum pattern for each ROI of the object image. An analyzing module for object spectrum feature is to search for a second candidate object from data bank and to further analyze a match level between the real-object and the second candidate object. A fusion module further analyzes information of image feature and spectrum feature find whether or not having a matched object as an identify object.

System and method for object recognition

A system and a method for detecting multi-level intrusion events are provided. The system includes an area recognition module and an area classification module. The area recognition module performs a geometric topology operation to recognize a plurality of areas in a ground plane that has a plurality of boundaries and a plurality of gates, and each of the areas is constituted of at least one of the boundaries and at least one of the gates. The area classification module defines a plurality of security levels and classifies each of the areas recognized by the area recognition module as one of the security levels. Accordingly, the system is able to automatically recognize the areas in the ground plane, set the security levels of the areas, and generate the corresponding detection areas and tripwires according to the security levels of the areas.

System and method for detecting multi-level intrusion events and computer program product thereof

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Hsinchu, Taiwan

Ho-Hsin Lee