1118 results about "Heartbeat" patented technology

The present invention provides an FMCW broadband life detection radar breathing and heartbeat signal extraction algorithm. Compared with the prior art, the algorithm has the advantages that breathing and heartbeat signals of multiple persons can be obtained simultaneously, the boundaries and energy of reconstructed breathing signals can be very well kept by using Coiflets wavelets compared with traditional frequency-domain filtering, especially processing conducted on short-time signals is obvious, higher harmonics of the breathing signals are filtered out by adopting a double-coefficient based LMS self-adaptive filtering algorithm, and the self-adaptive filtering algorithm does not need additional reference signals. Due to the fact that a degressive search step size coefficient is adopted in the algorithm, the heartbeat signals can be better retained while breathing signal harmonics are filtered out, the heartbeat signals can be rapidly converged by selecting the appropriate search step size coefficient and adopting the double-coefficient based LMS self-adaptive filtering algorithm, and smaller stable imbalance is kept in longer time, so that finally separated heartbeat signals are more accurate in frequency component within a long time.

Methods for re-configuring a cluster computer system of multiple or more nodes when the cluster experiences communications failure. First and second nodes of the cluster have respective channel controllers. A SCSI channel and the controllers communicatively connect the multiple nodes. When a node becomes aware of a possible communications failure, the node attempts to determine the authenticity the failure and responds according to the determined authenticity. According to one method, a first node detects heartbeat node-to-node communications failure on the channel and then tests a physical drive on the channel. If the testing is successful, the node kills the other node. If the testing is unsuccessful, the first node commits suicide. In one embodiment, the coupling includes multiple channels communicatively coupling the first and second nodes and the first node selecting one of the channels for node-to-node communications. In this environment, choosing a physical drive involves testing node-to-node communications on another of the channels if no physical drive is online on the channel (and terminating the re-configuring method). If a drive is available, the first node uses the first physical drive online on the channel for testing. In another method, the second node initially detects communications failure and communicates that by attempting to negotiate wih the first node for a new configuration of the computer system. The first node tests a physical drive in response and negotiates with the second node if the testing was successful. If the testing was unsuccessful, the first node commits suicide.

The invention relates to a wearable flexible stress sensor and a preparation method and application thereof. Firstly, functional ink suitable for screen printing is prepared, and is printed on a wearable substrate through a screen printing method, and the stress sensor of a desired specification is produced. The stress sensor is used for monitoring physical deformation of stretching, bending, touching and the like from small ranges to large ranges, and has multiple application in the electronic skin fields and the biomedical application fields of human skins, expressions, pulses, heartbeats and the like, the human-computer interaction fields and the fields of virtual reality, entertainment technology and the like. The flexible stress sensor of the invention has the following advantages that the sensor has excellent stretching elasticity, and stretching strain can reach 100%; sensitivity is extremely high, and a sensitivity parameter (Gauge Factor) can be up to 8000 or more; linear relationships of working curves are excellent, stretching repeatability is good, and a stretching cycle lag is small; and a preparation process is simple, costs are low, massive integrated-device preparation is suitable, and application prospects are wide.

Some embodiments provide a method for detecting a failure of a layer 2 (L2) bump-in-the-wire service at a device. In some embodiments, the device sends heartbeat signals to a second device connected to L2 service nodes in order to detect failure of the L2 service (e.g., a failure of all the service nodes). In some embodiments, the heartbeat signals are unidirectional heartbeat signals (e.g., a unidirectional bidirectional-forwarding-detection (BFD) session) sent from each device to the other. The heartbeat signals, in some embodiments, use a broadcast MAC address in order to reach the current active L2 service node in the case of a failover (i.e., an active service node failing and a standby service node becoming the new active service node). The unidirectional heartbeat signals are also used, in some embodiments, to decrease the time between a failover and data messages being forwarded to the new active service node.

The invention provides a network human face recognition system with an intelligent management system, the system comprises a system management module and a plurality of recognition modules which are respectively in network connection with the system management module, wherein the system management module comprises a network data server and a management terminal which is in circuit connection withthe network data server; and the recognition modules comprise recognition control terminals and a plurality of electric control door locks, a plurality of acquisition modules and clients which are respectively in circuit connection with the recognition control terminals; and the clients comprise the functions of access control, attendance management and intelligent monitoring. The system management module can be connected with the plurality of the recognition modules and simultaneously control the plurality of the electric control door locks and the acquisition modules, thereby improving the scalability; the clients are arranged in the recognition modules, thereby proving more functional modules and improving the scalability of the system; and the recognition control terminals adopt the heartbeat mechanism, thereby realizing the periodic synchronous information interaction between the system management module and the recognition modules and ensuring the stability of the operation of the system.

The invention discloses a method for achieving high reliability of key equipment. The method comprises the following steps: deploying a first server and a second server; appointing an IP address, namely a floating IP shared by the two servers; mutually monitoring states of the two servers through heartbeat, and performing real-time data synchronization; when the first server is abnormal, updating the floating IP to the second server from the first server, and taking over the service of the first server from the second server through the floating IP.

The invention provides a redundant heartbeat link and opposite-end restarting link based double-controller storage system and belongs to the technical field of computer storage. Processors are connected through NTP (non-transparent bridge) and serial-port links, so that data mirroring and cache mirroring are realized and operating states of the processors can be mutually monitored in real time. When one of mainboards breaks down, another mainboard is capable of automatically repairing by restarting an opposite-end mainboard via a restarting link, even if one of the mainboards fails to self-repair, another mainboard also can completely take over all operations of the failed mainboard, and high reliability and stability of storage products are guaranteed.

The invention discloses a redundancy switching method among redundancy process control stations in a distributed control system, comprising the following steps of: implementing data synchronism among the redundancy process control stations via a redundancy network; respectively connecting each process control station and each engineer station to a switchboard via a network; sending heartbeat signals to the process control station in a standby state by the process control station in an activate state; setting up a system variable by the process control station; modifying the data of the system variable by the process control station in the activate state whenever executing a control logic; synchronizing the data of the system variable to the process control station in the standby state via a private network by the process control station in the activate state when synchronizing data to the process control station in the standby state; and judging whether the data of the variable in the synchronized data is the same with the last received one or not by the process control station in the standby state and judging whether the process control station in the standby state is activated. Through the method disclosed by the invention, the reliability of switching process control stations is improved.

The invention discloses an electrocardiogram data classification method and system combining feature extraction and an inception network. The method comprises the steps that 1, normalizing filtered electrocardiogram data; step 2, segmenting the processed electrocardiogram data obtained in the step 1; 3, performing feature extraction on the plurality of heartbeat segments obtained in the step 2; step 4, constructing an inception network suitable for the electrocardiogram data; 5, obtaining relative wavelet energy and wavelet energy on the whole electrocardiogram data and absolute average deviation of wavelet energy and heartbeat interval time of all heartbeat segments by calculation; and step 6, taking the integrated features as input of a pre-constructed multi-layer perceptron, training the multi-layer perceptron to a preset convergence condition, and obtaining a final classification model. According to the method, the model not only extracts very valuable expert features, but also considers deep features of the electrocardiogram data, so that the purpose of enhancing the robustness and classification capability of the model can be achieved.