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1st Reading
November 28, 2005 11:52 WSPC/170-JMMB 00163
Journal of Mechanics in Medicine and Biology Vol. 5, No. 3 (2005) 16 c World Scientic Publishing Company
SIMULTANEOUS ACQUISITION OF SIGNALS AND IMAGES: APPLICATIONS IN SPORTS MEDICINE AND NEUROLOGY
IVAN CORAZZA , MATTEO BOTTEGHI, CORINNA TERENZIANI and SEBASTIANO ZANNOLI Institute of Cardiology, University of Bologna, Bologna corazza@med.unibo.it PASQUALINO MAIETTA LATESSA and CLAUDIO TENTONI Faculty of Motor Sciences University of Bologna, Bologna

Accepted 1 January 2005

In some medical applications, the simultaneous acquisition of signals corresponding to physiological parameters and video recording allows a more accurate analysis of the problem and a more complete diagnosis. In rehabilitation, the correlation between parameters of interest (angles, speed, power, EMG) and images of the patients movements is important to devise an adequate training protocol. In neurology, some pathologies need to be investigated by a comparison of images and EEG signals. Nowadays, commonly used systems are made up of two dierent apparatuses: one for signals acquisition and one for video recording. They are separate pieces of equipment, and the integration between data and video is possible only to the detriment of information and the possibility to make quantitative analysis. This paper describes a new digital system for the concomitant acquisition of signals and video. It is a low cost instrumentation, PC based and easy-to-use. Data and video are recorded in standard formats and can be analyzed in a post-acquisition stage. The time resolution of the system is given by the video frame rate (25 fps), although an A/D conversion system allows frequencies up to 8000 Hz. The prototype was tested to verify synchronism between data and frames, and dierences smaller than the resolution (40 ms) were found. The feasibility of the system was checked in two dierent applications: rehabilitation training with an isotonic Leg Extension and a daily EEG examination of one patient at the Neurological Institute of Bologna University. Both the applications gave good results in terms of time resolution, synchronism and user-friendliness. Keywords: Digital imaging; A/D conversion; simultaneous acquisition of signals and video.

Corresponding

author. 1

I. Corazza et al.

1. Introduction The simultaneous analysis of movement and related physiological parameters is an important requirement in some medical elds, such as rehabilitation, sports medicine and neurology.1,2,3 Nowadays, standard procedures for rehabilitation and training are based on the subjective approach of the trainer who looks at the movement and corrects it on the basis of personal experience.1 The simultaneous acquisition of signals (angles, speeds, power) and images allows the trainer to correlate the physiological behavior with the movement, and a more adequate training or rehabilitative protocol can be devised on the basis of measurements besides subjective evaluation. In neurology, clinical practice often provides acquisition of EEG signals and video monitoring of the patient during particular procedures.3,4,5 Current systems consist of a traditional multichannel monitor and two cameras: the rst that looks at the patient and the second one that looks at the paper with EEG in output of the polygraph. In a post-acquisition phase, the image sequence of patient and EEG are mixed in the same lm. The result is an analogical video which shows patient images and EEG signals, useful to correlate the patients movements with electrophysiological signals, but precluding any measurements. The aim of this study is to describe a new system (ASSAI) for simultaneous acquisition of signals and images. The prototype has been tested for the acquisition of leg movements during sports training, and for monitoring a standard neurological procedure.

2. Methods

ASSAI is PC based system equipped with an A/D interface, a video card adapter and software for the management of data in dierent forms (analog signals, video signals).6 Analog signals acquisition is performed by Light Module, a digital device which can acquire up to 16 channels, with a resolution of 12 bit and a sampling frequency from 500 Hz to 8000 Hz. A serial communication interface connects the module with a personal computer (Intel PIII 700 MHz) equipped with an audio/video capture card (AV Master, Fast Multimedia), and with a maximal rate of 25 fps, PAL standard. This PCI card has an internal CPU that controls video acquisition, allowing a better performance of video recording. The interface is tted with a direct analog video output to monitor the input video signal on the VGA monitor during acquisition (PCI bus mastering PCI overlay) (7). The calculator is equipped with two VGA video outputs, allowing the concomitant management of two monitors; one for physiological signals and the other for video images. A Visual Basic r program manages each module through two specic driver libraries. Data are recorded in standard formats: signals are stored in binary coding and each datum takes two bytes. For video les, AVI format is used. This choice allows video spatial resolution ranging from to pixels. The software can manage the video output over 1 or 2 monitors in dierent denitions

Simultaneous Acquisition of Signals and Images
with an autosense feature. A digital camera (Panasonic NV-DS29EG), connected to the AV master by a SVGA cable, has been used as video source. A post-processing program allows the complete management of data. The activation (start up) of video and signal capture is managed in sequence by the computer and the synchronism between data inputs needs to be resettled. For this reason, an acquisition of synchronous square wave signal and lighting led was performed (16 channels at 500 Hz and video at 25 fps). The test was stopped after three minutes and the time dierence between the led activation image and the square-wave was measured throughout the entire test. This system prototype was tested in the rehabilitation eld and in diagnostic neurological procedures. 2.1. Rehabilitation
A leg extension instrument (Air Machine Mod. 919 Tech), equipped with angles and force sensors for both legs, was interfaced with the Light System. The digital camera was set to acquire lateral images of the legs.
Fig. 1. Set up for the study of leg movements.
The acquisition system was set in order to record a video and eight analogical channels at a rate of 250 Hz. A series of exercise repetitions was recorded. The software performs multiple analysis to obtain the time course of power production by dierentiating the angles signals.2 2.2. Neurology application
During an epileptic seizure, a patient shows characteristic EEG signals, and his/her body moves in an apparently uncoordinated way. Recent studies4 have shown that, for a particular patient, there is a close correlation between EEG waves and movements in a sequence which is the same in subsequent seizures. The need to analyze EEG signals during the movements sequence makes current systems unsuitable. Our prototype, instead, records both signals and video, and allows dedicated postprocessing to analyze the seizure accurately.
To test this, the Light System was connected to the polygraph monitor (EEG4418 k Neurofax, Nihon Kohden Corporation) in use in the EEG Laboratory at the Neurological Institute of Bologna University. A patient undergoing a routine checkup was monitored by the acquisition of 10 EEG signals plus 1 ECG (sampling rate 500 Hz), and the corresponding video sequence (384 288, 25 fps). For both applications, the correctness of recording was also checked by comparing DAT and AVI le lengths.

3. Results

Synchronism between physiological signals and video frames was checked and veried. Figure 2 shows two images of the led switched on and o, as and the corresponding signals. The red line corresponds to the time position of the recording. Delays between light and signals were measured throughout the recording, and a mean dierence of 2 ms was calculated (standard deviation: 0.2 ms). This value is less than the time resolution of the video system (25 fps: 40 ms). Moreover, the comparison between the le dimensions highlights the correspondence between video and signal sequences, with a dierence of 25 ms. This value can be explained by the fact that when acquisition stops, physiological signal values are recorded but the last video frame can be lost. Identical results were obtained by acquisition of the exercises on leg extension (Fig. 3).

Fig. 2. Synchronism verication.

Angles

Angular speed
Fig. 3. Images corresponding to start and stop positions of an exercise repetition on the leg extension. The red line shows the correspondence between angular signals and video frames.
Fig. 4. EEG signals and video frame of a patient undergoing a standard examination.
Recordings performed at the Neurological Institute shows standard examinations without any epileptic seizure. Figure 4 shows an example of the acquired data. File lengths highlight the correctness of the test with a dierence of 30 ms. 4. Discussion
The ASSAI system represents a novel solution in research oriented medical technology. The system manages diagnostic procedures in a standard way and also permits personalized post processing of stored data, both in the form of analog signals and image sequence. The tests done to check the synchronism between analog and video signals gave good results with a time delay shorter than the resolution of the video system (40 ms). Video and data les length corresponded, and no frame was lost
during recording. The software measures signals and correlates them with frames and, vice versa, analyzes the sequence of video frames to obtain biomechanical information. An improvement of this prototype will be the development of a program for automatic image analysis and real time pattern recognition, to analyze movements easily during the examination. Current technology can also increase the video frame rate, allowing the analysis of rapid movements such as Parkinson tremor. This will be the next step.

Acknowledgment

The authors express their gratitude to Air Machine S.r.l. for technical support.

References

27 1. Ishida A, Description and measurement of anatomical joint motion, Front Med Biol Eng 5(3):161173, 1993. 2. Tentoni C, Maietta PL, Brasili P, Corazza I, Zannoli S, Mondardini P, Zannoli R, Analisi funzionale del movimento su apparecchio isotonico Leg Extension mediante analisi di posizione angolare, velocit` angolare e forza istantanea, Medicina dello Sport a 57(2):173, 2004. 3. So EL, Penry JK, Epilepsy in adults, Ann Neurol 9(1):316, 1981. 4. Tinuper P, Grassi C, Bisulli F, Provini F, Plazzi G, Zoni E, Lugaresi E, Split-screen synchronized display. A useful video-EEG technique for studying paroxysmal phenomena, Epileptic Disorders 6:2730, 2004. 5. Li Z, Martins da Silva A, Cunha JP, Movement quantication in epileptic seizures: A new approach to video-EEG analysis, Trans Biomed Eng 49(6):565573, 2002. 6. Zannoli R, Maietta PL, Corazza I, Zannoli S, Botteghi M, Mondardini P, Tentoni C, Sistema per lacquisizione simultanea di segnali analogici ed immagini per lanalisi funzionale del movimento della gamba, Sport: wellness, tness or business?, Medicina dello Sport 57(2):174, 2004. 7. Fast Multimedia AG: Manuale AV Master, Febbraio, 1999.