File size is limited by the restraints of the operating system and the available memory space on your hard drive or disk (depending to which you save the file). Software for Windows and MacOS may have different limitations due to system restrictions.
Current release: AcqKnowledge 5.0.2 – 64 bit and Biopac Student Lab 4.1.2 – 32 bit
There are multiple cases (configs) related to the issue of Memory/HardDrive/32bit-64bit limitations
All released versions have the same single limit applied to channel(s) length in SAMPLES. Channel length is limited by 2 Giga Samples = 2,147,483,648 samples
Any EDIT functions (copy/paste, resampling, merging, duplicate channel, remove waveform, cut selected data area) cannot jump over this 2 GigaSamples limit
Acq 5.0.2 64-bit offers big improvements in terms of file size and memory limitation
Acq 5.0.2 can read/save data files of virtually unlimited size in bytes.
The only limitation is free hard disk space.
Acq 5.0.2 cannot avoid 2 GigaSamples limit per channel, but can handle 100+ calculation/transformation channels (8 bytes per sample).
Example: Acq 5.0.2 was tested with data files of about 45 Gbytes – 4 analog channels + 4 calc channels, length is about 1.1 GigaSamples
Acq 5.0.2 utilize 2 features – 64-bit addressing and Virtual memory supported by Windows – and allow to handle data file which size is limited by Physical RAM and Virtual Memory settings of Windows OS.
Acq 5.0.2 can allocate ALL physical RAM of the computer to load data into the memory for transformations, and also can utilize virtual memory of the computer.
Using of virtual memory for transformations or “load all data into memory” is very helpful – it does not limit user to transform extremely long data channels with annoying prompt “Not enough memory to execute transformation.”. However, user should expect delays with transformations because virtual memory means using hard drive as memory substitute.
Example: Computer has 16GB of RAM and virtual memory configuration for PAGE FILE is set to Initial size = 24GB and Max size = 48GB. Under this setting, Acq 5.0.2 can load into the memory data file of about 16G + 48Gb = 64 GB (minus memory allocated by OS Windows and other processes)
File and memory functions are unchanged at 2 GigaSamples of length and 4 GBytes of file size. BSL 4.1.2 can allocate max 2 GBytes of RAM for transformations.
Use the following equation to calculate the memory required for your acquisition:
Memory required (bytes) = [(8C + 2A) x S x T] + 1 MB*
C = Number of calculation channels
A = Number of analog channels
S= Sample rate (samples/second)
T= Recording time (acquisition length)
* 1 MB = memory required to store file information
Journals, events, and other information are variable and will also require more disk space. Once analog channels are filtered or otherwise transformed, the required amount of storage will increase to 8 bytes per sample, identical to calculation channels. It is not possible to perform any transformations for acquisitions where converting analog channels to floating point will exceed 2 GB.
Refer to the software guide available under the program Help menu for setup and analysis guidelines when working with large files.
The fEMG Electromyography Smart Amplifier is designed specifically for recording facial EMG signals and electrical activity from other small muscle groups. Use with AcqKnowledge™ software to analyze facial expressions and startle paradigms. BIOPAC’s new Smart Amplifiers are designed for great data. Smart Amplifiers improve performance by amplifying the physiological signal close to the subject, which allows a high-level […]
Recent psychophysiological studies feature BIOPAC’s MP Research series of Data Recorders and AcqKnowledge software. Creating Adaptive Assistants for helicopter crews based on Real-time Physiological Data In the Mercedes S-Class, biometric tools track a driver’s eyes, heart rate, and other physiological data, with one goal in mind: Making sure drivers are alert and safe on the […]
BIOPAC’s just released Introductory ECG Guide addresses fundamental to advanced concerns to optimize electrocardiography data recording and analysis. Topics include: ECG Complex; Electrical and Mechanical Sequence of a Heartbeat; Systole and Diastole; Configurations for Lead I, Lead II, Lead III, 6-lead ECG, 12-lead ECG, precordial leads; Ventricular Late Potentials (VLPs); ECG Measurement Tools; Automated Analysis Routines […]