A new multisensor software architecture for movement detection: Preliminary study with people with cerebral palsy

Molina, Alberto; Guerrero, Jaime; Gómez, I.; Merino, Manuel

doi:10.1016/j.ijhcs.2016.08.003

Cited by 5 publications

(6 citation statements)

References 36 publications

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“…With a similar filter length, this software has been used to implement a low pass filter with zeros at 100 Hz to guarantee the reduction of the lighting interference when using an infrared system to detect blinks [ 45 ]. The polyphasic filter class has also been used in [ 35 ] to apply a 64-tap low pass filter, with a decimation factor of 16, in order to smooth the three-axis data of an accelerometer in order to detect movements in children with cerebral palsy.…”

Section: Discussionmentioning

confidence: 99%

“…By segregating an application into layers, developers can modify or add a specific layer, creating flexible and reusable code, instead of having to rework the entire application. Several studies have included this multilayer architecture in their designs [ 35 , 45 ].…”

Section: Software Architecturementioning

confidence: 99%

“…Arduino boards containing 32-bit processors, such as Due or Uno32 have been used for different real-time applications: audio [ 28 ], finite or infinite impulsive impulse digital filters [ 29 ], image compressing [ 30 ] or for detecting R waves in electrocardiogram signals [ 31 ]. Nevertheless, boards based on 8-bit processors have been successfully used in biomedical applications such as cardio monitoring [ 32 ], online heart-rate detection [ 33 ], amputee rehabilitation [ 34 ], or for movement detection in people with disabilities based on the processing of signals delivered by accelerometers or flexometers [ 35 ]. As such applications do not need to process a large amount of data, the time constraints for real-time processing are more relaxed than in audio or video applications.…”

Section: Introductionmentioning

confidence: 99%

“…This software is an evolution of a previous work [ 35 ] where a five-layer software architecture for movement detection was proposed. That software contains low pass filters, guarantees sampling rate, includes a K-means algorithm and a finite state machine using software timers.…”

Section: Introductionmentioning

confidence: 99%

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Real-Time Processing Library for Open-Source Hardware Biomedical Sensors

Molina

Castro-García

Lebrato-Vázquez

et al. 2018

Sensors

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Applications involving data acquisition from sensors need samples at a preset frequency rate, the filtering out of noise and/or analysis of certain frequency components. We propose a novel software architecture based on open-software hardware platforms which allows programmers to create data streams from input channels and easily implement filters and frequency analysis objects. The performances of the different classes given in the size of memory allocated and execution time (number of clock cycles) were analyzed in the low-cost platform Arduino Genuino. In addition, 11 people took part in an experiment in which they had to implement several exercises and complete a usability test. Sampling rates under 250 Hz (typical for many biomedical applications) makes it feasible to implement filters, sliding windows and Fourier analysis, operating in real time. Participants rated software usability at 70.2 out of 100 and the ease of use when implementing several signal processing applications was rated at just over 4.4 out of 5. Participants showed their intention of using this software because it was percieved as useful and very easy to use. The performances of the library showed that it may be appropriate for implementing small biomedical real-time applications or for human movement monitoring, even in a simple open-source hardware device like Arduino Genuino. The general perception about this library is that it is easy to use and intuitive.

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Section: Discussionmentioning

confidence: 99%

Section: Software Architecturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Real-Time Processing Library for Open-Source Hardware Biomedical Sensors

Molina

Castro-García

Lebrato-Vázquez

et al. 2018

Sensors

View full text Add to dashboard Cite

show abstract

“…It is not always easy for the experimenter to collect data and synchronize them with experimental phases, time intervals or simple events, when several devices and programs are running at the same time, as with multimodal interfaces [20]. To illustrate this, in [27], [26] two different systems were proposed to allow people with disabilities to access a computer. The former modulates the level of attention through an electroencephalography (EEG) sensor, whereas the latter requires residual movements detected by accelerometers or flex sensors.…”

Section: Introductionmentioning

confidence: 99%

An Easy-to-Use Multi-Source Recording and Synchronization Software for Experimental Trials

et al. 2020

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A typical routine in many scientific studies consists of recording data from devices and identifying which segment of data corresponds with an experimental interval. However, many current applications have been designed to obtain and save data from one single device, and synchronizing data with the markers that delimit the test phases can be difficult. To address this issue, we have developed LSRec, which is based on Lab-Streaming Layer, a C++ library that allows data synchronization. LSRec is an easy-to-use, open-source, multi-platform, recording system developed on Java that can save data from several devices at the same time, while maintaining synchronization with the experimental phase markers. It supports three explicit sync methods: the first uses one-integer-channel input Lab-Streaming Layer streams. The others use TCP/UDP socket messages and allow any existing software that generates sync markers through TCP/UDP messages to be used under the same conditions. In LSRec, the markers are saved together with input data, facilitating the process of linking data with test stages. A prerequisite for recording software is to guarantee suitable timing performance, with no data loss and an easy user interface. These features were assessed for LSRec, with no data loss detected for 20 hours (25 sessions). We evaluated performance by measuring timestamp deviations for sync marker and input data. The sync methods exhibited an average of deviations of around −34µs (which is more than acceptable, e.g., in studies involving living beings), whereas the absolute value of deviation for one-channel data was lower than 40µs. Finally, we assessed the system's usability with the technology acceptance model 3 survey (6 volunteers). Subjects saw the software as useful, and intended to use it in the future. In conclusion, LSRec is a useful tool for those who need to record data from multiple sources, and maintain synchronization with experimental phases with low delay.

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Communication Technologies Based on Voluntary Blinks: Assessment and Design

et al. 2019

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Some people with severe disabilities are confined in a state in which communication is virtually impossible, being reduced to communicating with their eyes or using sophisticated systems that translate thoughts into words. The EyeTrackers and Brain-Computer Interfaces (BCIs) are suitable systems for those people but their main drawback is their cost. More affordable devices are capable of detecting voluntary blinks and translating them into a binary signal that allows the selection, for example, of an ideogram on a communication board. We tested four different systems based on infrared, bioelectrical signals (Electro-Oculography (EOG) and Electro-Encephalography (EEG)), and video processing. The experiments were performed by people with/without disabilities and analyzed the systems' performances, usability, and method of voluntary blinking (long blinks or sequence of two short blinks). The best accuracy (99.3%) was obtained using Infrared-Oculography (IR-OG) and the worst with the EEG headset (85.9%) and there was a statistical influence of the technology on accuracy. Regarding the method of voluntary blinking, the use of long or double blinks had no statistical influence on accuracy, excluding EOG, and the time taken to perform double blinks was shorter, resulting in a potentially much faster interface. People with disabilities obtained similar values but with greater variability. The preferred technology and blinking methods were Video-Oculography (VOG) and long blinks, respectively. The several Open-Source Hardware (OSHW) devices have been developed and a new algorithm for detecting voluntary blinks has also been proposed, which outperforms most of the published papers in the reviewed literature.

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A new multisensor software architecture for movement detection: Preliminary study with people with cerebral palsy

Cited by 5 publications

References 36 publications

Real-Time Processing Library for Open-Source Hardware Biomedical Sensors

Real-Time Processing Library for Open-Source Hardware Biomedical Sensors

An Easy-to-Use Multi-Source Recording and Synchronization Software for Experimental Trials

Communication Technologies Based on Voluntary Blinks: Assessment and Design

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