Electroencephalography and clinical Neurophysiology, 82 (1992) 239-247

239

© 1992 Elsevier Scientific Publishers Ireland, Ltd. 0013-4649/92/$05.00

EEG 91063 R e v i e w article

D e s i g n p r i n c i p l e s for c o m p u t e r i z e d E E G m o n i t o r i n g Ronald P. Lesser a,b W.R.S. Webber and Robert S. Fisher a~. Johns Hopkins Epilepsy Center and Departments of Neurology and " Neurosurgery, Johns Hopkins Uni~'ersitySchool of Medicine, Baltimore, MD 21205 (U.S.A.), and t, The Zanl,yl Krieger Mind/Brain Institute, Johns tlopkins Unit,ersity, Baltimore, MD 21218 (U.S.A.)

(Accepted for publication: 30 December 1991) Key words: Digital electroencephalography; Computerized monitoring; Computer based medical systems

Approximately 60 years ago Hans Berger first recorded E E G in humans. Modern electroencephalographers have modified this useful technique in many ways, but the preponderance of recordings are still tracings on p a p e r and are obtained and displayed in a way relatively unchanged from Berger's time. Digitally based acquisition and analysis have long been used for evoked potentials, but it only is in recent years that commercial vendors and individual laboratories have developed digital E E G recording systems (Ives et al. 1976, 1991; G o t m a n et al. 1985a,b; Lopes da Silva et al. 1986; Burgess et al. 1989; Kaplan and Lesser 1990; Lesser et al. 1990; Panych and W a d a 1990). Standards for use and interpretation of these systems are emerging (American E E G Society 1986, 1991; A S T M 1991). As with any new technology, there is the potential for confusion and misuse. The clinician easily can become mired in the details of technology and lose sight of the goals and principles that should guide E E G studies of any type. At our institution we have had the opportunity to design and use a computerized seizure monitoring system based upon general purpose computers. Many such systems have been developed. Our own experience has given us a sense of general principles that are important to both designers and users of systems for digital electrophysiology. We will use illustrations from our own system and, therefore, often will emphasize issues pertinent to seizure monitoring. Our institution, however, presently is building an outpatient building which will be several blocks from the main E E G lab. Our plan is tor this to be a fully digital laboratory as

Correspondence to: Ronald P. Lesser, M.D., 2-147 Meyer Building, Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Baltimore, MD 21205 (U.S.A.). * Present address: Barrow Neurological lnsitute, Phoenix, AZ, U.S.A.

well, so we have given considerable thought to how our experience with digital long-term seizure monitoring might be applied to the routine E E G / e v o k e d potential laboratory. These considerations suggest that there are a number of basic, often interrelated, principles (Table I) which are common to different types of electrophysiologic recordings. We recognize, however, that our system and the design principles we derive from it represent only one possible implementation.

C h a r a c t e r i s t i c s o f an ideal system

(1) The system should be easily constructed f r o m available and affordable components, such as personal computers and basic peripherals

Microprocessor based system design ideally proceeds from task to software to hardware. In clinical neurophysiology, the tasks are highly variable, including EKG, E E G , evoked potentials, epilepsy monitoring and other physiological recordings of from 1 to over 100 channels, for periods lasting fractions of a second to weeks. In some cases, software may come bundled with dedicated hardware as a "turnkey" system, in

TABLE I Design principles for digital electrophysiology. 1 Affordability 2 Expandability and flexibility 3 Redundancy 4 Modularity 5 Functional separation 6 Simplicityof communication 7 Convenience 8 Compactness and convenience of storage 9 Usability 10 Human validation

240

R.P. LESSER ET AL. A

---ID,,~

c

~_~ ~

.~,~,~i

03-01

o~o6

e

11-12

13-14

Fig. 1. Basic elements of digital neurophysiologic acquisition. The patient (a) is attached to a group of amplifiers (b), up to 128 in some applications. These in turn are attached to a computer (or computers) devoted to data acquisition (c). Data review can take place on this computer, be transmitted or carried to a separate data review computer (d) or to a file server (e) which in turn sends EEG, evoked potential, sleep, or other electrophysiologic information to the dala review computer. Information can be stored in a variety of ways, but optic disks and magnetic tape are particularly well suited for mass storage (f). Additionally, patients may be on videotape (g). In this case there must be time linking between the video recording unit and the data acquisition computer.

others, as separate items which can be installed on general purpose computers. Institutions also may choose to write their own software packages. Over the past decade the personal computer has become immensely more powerful, with increased processing speed (from about 4.77 M H z in 1981 to 50 MHz in 1991), memory, and visual display resolution. We have benchmarked the speed of math processing on computers in our laboratory over the last 3 years using a multiply and accumulate function. The speed of performance has increased 40-fold from the 10 MHz 80286/80287 to the 33 M H z 80486. Display resolution of standard monitors for the IBM PC and its clones has increased 4-fold from the 320 × 200 C G A to the 1024 × 768 Super-VGA. Higher resolutions are easily available. Similar improvements have occurred for the Macintosh, for X-windows and other workstations, and for

Fig. 2. Seizure onset, recorded from subdural electrodes and printed using a standard office laser printer. One advantage of digital EEG is that the data can be manipulated and redisplayed. In A and B a seizure onset can be seen, as recorded by subdural electrodes. The background EEG is replaced by rhythmic delta and then by faster frequency activity (dot). The fast frequency activity is followed after several seconds by repetitive spikes, best seen in B. In C the EEG in 4 channels has been enlarged in size so that the components at seizure onset can be visualized more clearly. Each figure represents a subset of the 64 channels which were acquired. The others are not displayed in the interests of clarity. The dot indicates the same point in time in all 3 sections.

' I~¢

B ~3-~

43-.

....

59"~

03-01

07~0S

13-14

|

i,

DESIGN PRINCIPLES FOR C O M P U T E R I Z E D M O N I T O R I N G

other platforms. Commonly available hard disks have increased from 10 to 20 Mbyte units with 60 msec disk access times to 300 (or more) Mbyte units with 14 msec access time. Improvements in all aspects of microprocessor technology now allow the basic hardware for electrophysiology acquisition to cost $10,000-$50,000 per unit depending upon the need for special data acquisition or processing boards, for software, for a separate data review station or for video. It is true that useful monitoring systems can be based upon minicomputers (Burgess et al. 1989) or even mainframes serving several patients on a time-sharing basis. Although such an approach is workable, the need to split the attentions of the computer between several patients can impose a significant burden on all but the largest machines. Another alternative would be to devote a number of small microprocessors or microcomputers to each patient, with each devoted to a single separate task (Ives et al. 1991). However, the need for interprocess plus intermachine communication and synchronization can impose a significant added level of complexity to the system as a whole. Microcomputers now can contain multiple processors within a single unit, simplifying this. We, therefore, believe that linked small computers, each devoting one or more processors to the analysis of a single patient, presently provide the most economical approach to computerized E E G monitoring, and the one with the greatest modularity and growth potential. Affordability is an issue of not only initial cost but also of long-term upkeep. Moreover, the difficulties in "debugging" a complex electrophysiologic system can be substantial, with some of the wrinkles almost inevitably smoothed out after delivery to the end-user. Vendors of commercial systems therefore should have responsive policies with respect to hardware and software maintenance which recognize this, should rectify flaws quickly, and should not seek to shift the responsibility for a system's integrity and development to the user. Conversely, users should have realistic expectations regarding the capabilities of purchased systems.

(2) The number of data channels which can be acquired for each patient should be expandable and flexible Within the limits of maximal data intake the system should be flexible regarding the number of patients recorded (e.g., 20, 32, 64, or 128 channels for 1 patient), and regarding the types of data recorded (EEG, EKG, oximeters, special transducers). Amplifiers record biological signals in analog form. These must be digitized for use by computers. The digital sampling rates necessary for these tasks can be quite variable. In the case of E E G , voltages can be represented adequately with a dynamic range of 70 dB. This requires 11 or 12 bits (2048 or 4096 voltage steps) of

241

resolution by the analog to digital converters which accomplish this. In the frequency domain, auditory evoked potential recordings commonly obtain 512-1024 s a m p l e s / c h a n nel for 10 msec whereas 200 s a m p l e s / s e e are usually adequate for conventional EEG. For 64 channels of E E G , each sampled at 200 samples/sec, the total digitization rate would be 12,800 data points (25,600 bytes)/sec. In special circumstances requiring analysis of high frequency E E G components higher sampling rates are desirable (Fisher et al. 1991). Individual machines will have hardware and software determined upper limits of data acquisition, storage and analysis rates. Within these limits there should be user-determined flexibility. Each of these choices should be obtainable by a user with a minimum of technical knowledge, and there should be sensible default settings. As an example, in the Johns Hopkins Epilepsy Monitoring Unit we typically digitize approximately 3 min before and 1 rain after a seizure is recognized. We sample up to 64 channels at a rate of 200 s a m p l e s / s e c with 12-bit (4096-point vertical) voltage resolution. This allows a clear E E G screen image (see below), and a disk file size of about 6 Mbytes.

(3) There should be redundancy in the system Redundancy affords several advantages: (a) in the case of breakdown of one part of the system another can be substituted at least on a temporary basis; (b) if data capture does not occur through one means it can be accomplished through another; and (c) no single point failure can cause the whole system to become inoperable. The practical implementation of many of these concepts will be familiar to computer users. When first capturing data, save in more than one place, for example to a floppy disk and a hard disk, or back-up on cartridge tape. If computers are linked together into a network, save both on the local computer and on the file server, until you are sure of data integrity on the server. Consider recording to two separate disks on the server. This is one area where newer and older technologies can be combined easily: data can be acquired onto analog tape at the same time as it is acquired and analyzed by computer based systems (cf., Ebersole et al. 1985; Kellaway and Frost 1985).

(4) The system should be modular, with relatit,'ely standard parts throughout and ideally with one processor system per patient Individual dedicated computers help to ensure that a breakdown in data acquisition from one patient does not lead to catastrophic loss of data from all patients. Adding more acquisition or review stations would

242

merely require adding an additional module to the system. The implementation of a system with individual, separate, basic modular subsystems is relatively straightforward. A more difficult issue is how to expand functions within a given module. Modularity means that it should be possible for the user to add additional algorithms into the acquisition or analysis protocols. A user for example might want to use a particular method of filtering or analyzing data in a particular situation. In many cases this might be accomplished by changing the controls within the existing software package but, in others, a new algorithm might be necessary. Because commercial implementations cannot always keep pace with scientific advances, the devices should allow for the user to add particular algorithms which might be written at the user's location. This in turn dictates several other requirements. The first is that the software utilized in the computer should be written using relatively standard operating systems and standardized languages, particularly C, or allow easy access into the systems for software written using standard languages. Given the practical complexities of digital electrophysiologic systems, certain types of modifications are best made by the manufacturer or p r o g r a m m e r who designed the original system. Therefore, such accessibility cannot be absolute, especially in the case of real time data acquisition. Nonetheless, there should be ways of designing programs which allow a reasonable accommodation between the need to develop a successful initial h a r d w a r e / s o f t w a r e platform and the need to allow later on-site modifications to meet clinical or research needs.

(5) There should be functional separation between data capture, data analysis, and data storage functions so that enhancements to one function do not require modifications to other parts of the system The ways in which hardware and software developments allow the data to be manipulated are likely to continue undergoing rapid changes. H e r e a new algorithm may allow better analysis of evoked potentials during intraoperativc monitoring, there a special purpose processor may facilitate seizure detection. New procedures and protocols may allow greater levels of data reduction and thus allow more data to be stored in less space for either temporary or archival purposes. Appropriate hardware and software design should allow one to modify one step in the overall process, or to take advantage of conceptual and technical improvements with a minimal amount of modification of the system as a whole. Storage needs vary according to the task. In our epilepsy monitoring unit data are stored as 2 b y t e s / s a m p l e to save processing time, and also to

R.P. LESSER ET AL.

allow for 16 bits of resolution should that ever be needed. These requirements generate a need to process about 1.5 Mbytes of d a t a / m i n / p a t i e n t in the case of 64 channels of E E G (or about 25,600 bytes/sec). This is a great deal of data, but the basic acquisition and storage of this volume of data are well within the capabilities of existing technology.

(6) There should be simplified communication among system modules and between laboratories In most contemporary E E G laboratories recording occurs onto paper which is then physically carried to the electroencephalographer for review. After review the record is stored in still another location. Microprocessor based technologies should imitate the functional separations among acquisition, review, and storage, but perform them with greater efficiency of time and space. Data of interest ( E E G seizures, spikes, evoked potentials, events of apnea, etc.) detected by a computer acquiring information from a patient should automatically be made available to the reader for confirmation or analysis. Easy communication also means that it should be simple to go from the stage of the technologist acquiring data to the stage of the reader reviewing the data to the stage of archival storage. Finally, it should be possible to allow digital data from one laboratory to be analyzed and reviewed in another. This would require a standardized format or method which could be used to transmit or translate data. Various techniques can be used to allow portability of electrophysiologic and other data among the different components of a computerized monitoring system. Network "protocols" such as ethernet are commonly available in hospital and large clinic environments, and may serve as a framework for transfer of data among different machines. Speed, reliability and avoidance of simultaneous conflicting changes affecting a record become priorities in designing networks for electrophysiologic data. Telephone transmission has been used to convey E E G analog data, but this method is prone to introduction of artifact through the telephone system (Brittenham 1986). Digital transmission of data by modem is more reliable, but still slow. At 2400 baud, a 1 Mbyte E E G file would require over 1 h to transmit. Although the theoretical limits of current ethernet protocols are as high as 10 Mbytes/sec, rates of 50-200 k b y t e s / s e c are more realistic in real world applications. Still, this means that a 1 Mbyte file might travel over a computer network in less than 15 sec. As an alternative to networks, data can be placed by the acquisition system onto optic disk, floppy disk, removable hard drives, cartridge tape, or other transportable media and hand carried to the review station. In our seizure monitoring unit all machines are "wired" together, and data are automatically transferred using a

DESIGN PRINCIPLES FOR COMPUTERIZED MONITORING networking protocol from the machine which has acquired the data to the separate machine which will be used for review. Once the data are reviewed, they are automatically stored on optic disk. All these steps are, in a sense, tedious to accomplish, but machines excel in their ability to tolerate tedium and in their reliability in accomplishing repetitive tasks. The same is not always the case for humans. Although digital etectrophysiology is a potentially paperless system, there is still a role for paper output as a machine-independent and universally transportable format. Equipment available allows such a printout to be performed with higher resolution (finer lines) than is the case with conventional LEG. In our laboratory we utilize a standard office laser printer to print examples of individual spikes, seizure onsets, and other brief E E G phenomena. Other laboratories use special purpose laser printers (Jacobs et al. 1989, 1991a) or high resolution continuous thermal printers which output continuous E E G tracings, very similar in their appearance to conventional paper EEG. Different laboratories should be able to share data files, regardless of what machine each of us happens to be using. There is currently an ongoing effort within the neurophysiology community, including both manufacturers and users by a committee of The American Society for Testing and Materials (ASTM) which is addressing itself to the creation of both hardware and software standards for neurophysiologic recordings (ASTM 1991; Jacobs et al. 1991b). This should eventually lead to the creation of acceptable standards for both acquisition and review of data and, in particular, for interchange of data among laboratories. When LEGs, polysomnograms, or evoked potentials are shipped using an agreed upon standard, the receiving lab will be able to review the data using this standard or translate the data from the standard into the format used locally. In the past when an L E G from one laboratory had to be reviewed in another, it was necessary to ship bulky and expensive paper records. It always was possible that the record might be lost. Photocopying was an alternative, but an extremely cumbersome one. In the future it will be possible to accomplish the goal of sharing data by copying it quickly and shipping it compactly (see section 8) using digital media. It is simpler to copy digital records onto floppy disks, optic disks, or tape than to copy paper records onto still more paper. (7) Computer aided E E G ret,iew should be at least as com~enient as is' the rez,iew o f paper tracings The speed of digital data presentation should be comparable to, and its appearance must be similar to, that of conventional paper E E G (Lesser et al. 1990;

243 Jacobs et al. 1991). This last point cannot be overemphasized, since E E G reading is a visual skill that suffers greatly when tracings look different - - even if the same information is present in an altered format. Care must be taken therefore to imitate conventional clinical time bases (30 m m / s e c ) , gains ( 7 / x V / m m ) and filters (0.3-70 Hz) in the default display modes. Readability of EEGs on modern high resolution digital screens can be excellent. When we first developed our own system, we were concerned that some users would find it difficult to evaluate L E G on a video monitor and would request a conventional paper EEG. We therefore provided for digital-to-analog paper playout of the data, onto standard L E G paper via a standard E E G machine. No one has ever requested such a playout. In practice, once accustomed to the format, most EEGers find digital format more convenient than paper, since they can change montages, gains, filters and time bases while reading the record. In general, digital E E G systems have used a single screen for all functions. For a few (perhaps up to 20-32) channels, this works relatively well, even though the L E G must share space with various program "menus." We have such a system in our laboratory. However, when more channels, or more time, need to be displayed on the screen, the graphic system should have a higher resolution and, ideally, the L E G would occupy virtually all of the screen. One way of accomplishing this second need which we have explored is to use two separate monitors, as is common in the C A D / C A M (computer aided d e s i g n / c o m p u t e r aided manufacture) approach used by designers and engineers. In our laboratory one screen is used for menus, topographic maps, signal analysis plots, and the like. The other is a high resolution monitor devoted exclusively to the L E G and on which we plot up to 64 channels of EEG. The E E G e r ideally should be able to " p a g e " forwards and backwards through the computerized data as quickly as through a paper record (Lesser et al. 1990). When reading a conventional paper L E G or polysomnogram record, the reader must turn each page by hand, a minor nuisance for routine 100-200 page outpatient EEGs and perhaps more of a nuisance in the case of 1000 (or more) page prolonged recordings. By comparison, the process of placing the data on the video monitor screen can take place automatically or at the press of a button. Other conveniences are possible. For example, in our system, the number of seconds or minutes of data on the screen can be increased up to 8-fold when appropriate. Conversely, when needed, the L E G can be "spread out" 4-fold on the screen, so that millisecond by millisecond interchannel relationships can be studied in greater detail. Just as one can flip back and forth between sections of a record which might be separated by 10s or 100s of

244 pages, it should be possible to flip quickly backwards and forwards through the electronic data. The reader should be able to tag particular sections of the record which he or she might need to refer to more than once during the reading session, or reaccess easily at another time. Similarly, in the case of other prolonged studies, such as might occur during intraoperative evoked potential monitoring, the computer program should facilitate comparisons between tracings acquired at different times, such as baseline evoked potentials, records obtained after anesthetic induction, and records obtained during critical periods of the procedure. In practice, this means that it should be possible to simultaneously display wave forms obtained at several different points in time, with each wave form appropriately labeled. During studies which compare across multiple conditions, as commonly is the case with cognitive or event-related potential studies, software should ease the task of performing comparisons across conditions or between patients.

(8) There should be data reduction, including both summarization of the captured information and storage by electronic media The computer should offer aids to calculation, measurement, and analysis not present with p a p e r records. We do not intend this to be a comprehensive introduction to the technique of digital signal analysis; many excellent such works are already available ( G o t m a n et al. 1985a; Lopes da Silva et al. 1986; Gevins and R6mond 1987). However, m e a s u r e m e n t of amplitude and frequency should be easy (no more misplaced rulers) as should m e a s u r e m e n t of standard signal parameters, such as root mean square power, interchannel correlations and coherence, or spectral power (fast Fourier transforms) ( G o t m a n 1981, 1983; Lopes da Silva et al. 1986; Gevins 1987; Gevins and R6mond 1987). Interchannel time correlations can be studied without confounding p a p e r pull or pen arc artifact. Faster frequency components of the L E G (Fisher et al. 1991) can be acquired and displayed. A screen cursor linked to a recorded clock time can line up events within milliseconds. Muscle artifact can be " r e m o v e d " from the recording (Gotman et al. 1981). Where electrophysiologic and video data are acquired simultaneously, microprocessor based techniques can be used to time-stamp both simultaneously. Off-line reformatting can be a major benefit of digital recording: it is no longer necessary to record multiple montages. If appropriately acquired, data can be obtained using a single " r e f e r e n c e " and later remontaged off-line digitally, using simple arithmetic manipulations, in whatever arrangement is appropriate to the analysis of a particular record. Attention must be

R.P. LESSER ET AL. paid to certain technical issues regarding method of sampling, interchannel amplitude matching, signal error and amplifier dynamic range when remontaging, but when properly done remontaging can be extremely useful. Similar advantages accrue to simultaneous L E G and video recording. With equipment from the analog era (Penry et al. 1975), it usually was necessary to acquire the L E G and video onto videotape in a fixed "split-screen" arrangement. What you saw was what you got. The L E G was frequently difficult to read and more channels of data might have been on the screen than would have been required to demonstrate a particular correlation. Current technology allows L E G and video to be acquired as separate "data streams" with reformatting of the L E G / v i d e o occurring after the fact, under the control of the reader, in whatever combination best elucidates the problem under review, Current so-called multimedia techniques even allow the video to be reviewed on the computer screen, under control of the computer. Digital systems should capture the kinds of data which the reader would have wanted to inspect during traditional paper readings, but also should summarize the captured L E G information in a clinically useful form (Lopes da Silva et al. 1977; Frost 1979, 1987; G o t m a n et al. 1979; Gotman 1982; Eberhart et al. 1989a,b,c,d; Guedes de Oliveira and Lopes da Silva 1990; Panych and Wada 1990). How symmetric is the background? Have basic frequencies changed over time? How many spikes have occurred over a 24 h period? Where were they located? When did seizures occur and at what electrodes did they appear to originate? For example, the computer should be able to analyze precisely the topographic distribution of an event such as a spike or sharp wave and present the results of this analysis to the reader graphically (Duffy et al. 1979, 1986; Guedes de Oliveira and Lopes da Silva 1980; Oken and Chiappa 1986; Duffy 1989). The computer also should "show" the reader what it is measuring so that the reader can make certain that the final graphical display reflects clinically relevant wave forms. When graphical displays or mapping techniques are used to summarize data it is important to recognize that such mapping techniques represent visual aids to the reader. They do not necessarily represent new data in themselves and they are only as good as thc analysis upon which the graphics are based (Oken and Chiappa 1986; Nuwer et al. 1987; Nuwer 1989). For example, when topographic maps are utilized to summarize or represent a portion of a record, the number of points representing " r e a l " data is equal only to the number of electrodes used in the recording. All other points on the maps represent extrapolations which may or may not accurately reflect the actual underlying physiology of the patient.

DESIGN PRINCIPLES FOR COMPUTERIZED MONITORING Just as important, storage by electronic media can save an enormous amount of space when compared to storage with paper. For example, if E E G s were recorded continuously on p a p e r for a single bed in a 24 h monitoring unit, this would require storage of 6 p a g e s / m i n of 16-channel EEGs, 8640 p a g e s / d a y , or over 3,000,000 p a g e s / y e a r . Over 6,000,000 pages would be generated by recording 32 channels and over 12,000,000 pages by 64 channels. Some data reduction is generally accomplished by judicious pruning of the record, saving seizures and spikes along with other appropriate sections. Nonetheless the paper storage needs would be considerable, and it would be necessary for someone to go through what could be a time consuming task of selecting and boxing the sections to be saved. In recent years an alternative means of long-term storage employed audio or video cassette tapes. Here again it usually was necessary to play out the data from the cassettes onto p a p e r for review, or copy the data one wished to save from one cassette to another for eventual storage (Ebersole et al. 1985; Nuwer et al. 1985; Sato et al. 1985). All of this "clipping" and storing can be done expeditiously and automatically using fully digital techniques. The space savings are considerable. One optic disk, with a storage size essentially that of a compact disk used in many home stereo systems, can save the equivalent of 12,000 pages of 16-channel EEGs. (9) The system should be easy to use including by a person with a minimum of computer experience and training. As many as possible of the system operations should be automatic and hidden from the user In our seizure monitoring unit the staffing of the data acquisition computers has been by nurses and by specially trained technicians who formerly were nurses' aides. None of these personnel had previous computer experience, but all easily learned to interact with the system. Computer operations should be largely hidden from the user. In our monitoring unit the computers are " n e t w o r k e d " so that all data are automatically moved over a wire link from the front end computers where the data are acquired to the back end computer where the data are reviewed. The front end of the computers are Unix based 680XO systems with two processors per machine and one machine per patient. The back end computer uses a DOS based 80X86 microprocessor, and these two kinds of computers organize data differently. A file format translation program therefore was written. It is invoked automatically and converts data between the file conventions used by each of the two types of machine (Webber et al. 1989; Lesser et al. 1990). Once the data are reviewed by the reader and the reader has indicated to the computer that they can

245 be saved, the saving of data also takes place automatically onto optic disk. The reader needs to know nothing about intricacies of data transmission but only needs to indicate that he or she wishes this transmission to take place. (10) El'ent-detection systems still require human t,alidation In traditional p a p e r based recordings technologists frequently will note sections of interest for later review. There currently are analogous software programs which identify, events of interest both for the analysis of sleep records and for the analysis of records of patients with epilepsy (Smith 1975; Frost 1978; G o t m a n et al. 1978, 1979; G o t m a n 1982, 1990; Bankman et al. 1988; Eberhart et al. 1989a-d; Panych and Wada 199(t; Murro et al. 1991; Ozdamar et al. 1991; Webber et al. 1991). Such programs can free the reader from many of the repetitive aspects of record assessment. However, most currently available spike and seizure detectors have significant rates of both false negative and false positive detections. Moreover, both human and digital marking are necessary: computer programs designed to recognize epileptic seizures automatically are unlikely to notice psychogenic episodes. The initial record could be summarized, events of interest could be grouped together for scrutiny by the reader and a preliminary assessment made, awaiting appropriate modification during the final reading. During p a p e r based recordings, the technologist might mark portions of the record which were contaminated by artifact and note the presence of external sources for the artifact such as chewing, intravenous drips, and the like. Similar annotations should be possible with digital data acquisitions (cf., Barlow 1986) if they are to fulfill the needs of electrophysiologic recordings. Both human and computer based annotations should be possible, and both should be easily available for subsequent review and modification. H u m a n review therefore remains very important, both from a medical and medicolegal perspective, although automated systems for both detection and display facilitate this review process.

Conclusion

No complex computer system will ever be perfect or final but it is clear that the current technology allows a system to have sufficient flexibility and adaptability to meet many needs. It should be possible to redesign systems as these needs and the available technology change. The benefits of a digitally based system include the ability to acquire and store prodigious quantities of data efficiently, to alter the appearance of the data at

24~

the time of the review, to apply algorithms for mathematical analysis, and to share data easily among various local and remote review stations. Disadvantages include initial costs and unfamiliarity of the system to those used to paper based techniques, although, as mentioned above, people seem to adapt readily. There is a requirement for at least a minimum of technical sophistication on the part of the user and support staff and a consequent need for initial and ongoing training. Training needs will be substantial until digital systems become more mature and "user-friendly." Nonetheless, in our experience, the advantages of digital based monitoring systems far exceeds their disadvantages. Over the next decade it is likely that a substantial proportion of recordings will be obtained using digital techniques.

References American Electroencephalographic Society. Guidelines for long-term neurodiagnostic monitoring in epilepsy. J. Clin. Neurophysiol., 1986, 3 (Suppl. 1): 93-126. American Electroencephalographic Society. Guidelines for Long Term Monitoring for Epilepsy. American Electroencephalographic Society, 1991. ASTM Standards Development Subcommittee E31.16 on Data Interchange of Electrophysiological Waveforms and Signals. Standard Specification for Transferring Digital Neurophysiological Data Between Computer Systems. American Society for Testing and Materials, Philadelphia, 1991. Bankman, 1., Webber, W.R.S., Waechter, M., Fisher, R.S. and Lesser, R.P. On-line detection of epileptic spikes on multi-channel recordings. Epilepsia, 1988, 29: 711. Barlow, J.S. Artifact processing (rejection and minimization) in EEG data processing. In: F,H. Lopes da Silva, W. Storm van Leeuwen and A. Rdmond (Eds.), Clinical Applications of Computer Analysis of EEG and Other Neurophysiological Signals. Handbook of Electroenceph. clin. Neurophysiol., Revised Series Vol. 2. Elsevier, Amsterdam, 1986: 15-62. Brittenham, D.M., Barlow, J.S., Boyer, S.W., Ghigo, J. and Henry, C.E. Guideline six: recommendations for telephone transmission of EEGs. J. Clin. Neurophysiol., 1986, 3 (Suppl 1): 23-25. Burgess, R.C., Jacobs, E.C., Collura, T.F., Turnbull, J.P., Liiders, H. and Klem, G.H. A computerized intensive EEG/video in-patient monitoring unit. J. Clin. Neurophysiol., 1989, 6: 367. Collura, T.F., Liiders, H. and Burgess, R.C. EEG mapping for surgery of epilepsy. Brain Topogr., 1990, 3: 65-77. Duffy, F.H. Clinical value of topographic mapping and quantified neurophysiology. Arch. Neurol., 1989, 46:1133-1134. Duffy, F.H., Burchfield, J.L. and Lombroso, C.T. Brain electrical activity mapping (BEAM): a method for extending the clinical utility of EEG and evoked potential data. Ann. Neurol., 1979, 5: 309 321. Duffy, F.H., Bartels, P.H. and Neff, R. A response to Oken and Chiappa. Ann. Neurol., t986, 19: 494-496. Eberhart, R.C., Dobbins, R.W. and Webber, W.R.S. Neural network design considerations for EEG spike detection. In: 15th Annual Northeast Bioengineering Conference, Boston, March 27 28, 1989a: 98. Eberhart, R.C., Dobbins, R.W. and Webber, W.R.S. CaseNet: a neural network tool for EEG wave form classification. In: Proc.

R.P. LESSER ET AL. IEEE Symp. on Computer Based Medical Systems, Minneapolis, MN, June 25-27, 1989b: 6/)-68. Eberhart, R.C., Dobbins, R.W. and Webber, W.R.S. Epileptiform spike/seizure detection using low-cost neural network tools. In: Annual Meeting of American Electroencephalographic Society, New Orleans, LA, Sept. 23-24, 1989c. Eberhart, R.C., Dobbins, R.W. and Webber, W.R.S. Neural network based systems for EEG wave form analysis. Epilepsia, 1989d, 30: 739. Ebersole, J.S., Manson, R.H., Williamson, P.D., Spencer, S.S. and Glaser, G.H. Monitoring at the West Haven VA/Yale University School of Medicine Epilepsy Center. In: J. Gotman, J.R. lves and P. Gloor (Eds.), Long-Term Monitoring in Epilepsy (EEG Suppl. No. 37). Elsevier, Amsterdam, 1985: 357-369. Fisher, R.S., Webber, W.R.S, Litt, B., Uematsu, S. and Lesser, R.P. High-frequency electroencephalogram activity at the start of seizures. Ann. Neurol., 1991, 30: 291. Frost, Jr., J.D. Microprocessor-based EEG spike detection and quantification. Int. J. Bio-Med. Comp., 1979, 10: 357-373. Frost, Jr., J.D. Mimetic techniques. In: A.S. Gevins and A. R~mond (Eds.), Methods of Analysis of Brain Electrical and Magnetic Signals. Handbook of Electroenceph. clin. Neurophysiol., Revised Series Vol. 1. Elsevier, Amsterdam, 1987: 195-2/19. Gevins, A.S. Correlation analysis. In: A.S. Gevins and A. Rfimond (Eds.), Methods of Analysis of Brain Electrical and Magnetic Signals. Handbook of Electroenceph. olin. Neurophysiol., Revised Series Vol. 1. Elsevier, Amsterdam, 1987: 171-193. Gevins. A.S. and R~mond, A. (Eds.). Methods of Analysis of Brain Electrical and Magnetic Signals. tlandbook of Electroencephalography and Clinical Neurophysiology, Revised Series Vol. 1. Elsevier, Amsterdam, 1987:683 pp. Gevins, A.S., Yeager, C.L., Diamond, S.L., Spire, J.-P., Zeitlin, G.M. and Gevins, A.H. Automated analysis of the electrical activity of the human brain (EEG): a progress report. Proc IEEE., 1975, 63: 1382 1399. Gotman, J. lnterhemispheric relations during bilateral spike-andwave activity. Epilepsia, 1981, 22: 453-466. Gotman, J. Automatic recognition of epileptic seizures in the EEG. Electroenceph. clin. Neurophysiol., 1982, 54: 530-540. Gotman, J. Measurement of small time difference between EEG channels: method and application to epileptic seizure propagation. Electroenceph. clin. Neurophysiol., 1983, 56: 501-514. Gotman, J. Automatic seizure detection: improvements and evaluation. Electroenceph. clin. Neurophysiol., 1990, 76: 317-324. Gotman, J., Gloor, P. and Schaul, N. Comparison of traditional reading of the EEG and automatic recognition of interictal epileptic activity. Electroenceph. clin. Neurophysiol., 1978, 44: 48-60. Gotman, J., Ives, J.R. and Gloor, P. Automatic recognition of interictal epileptic activity in prolonged EEG recordings. Electroenceph, clin. Neurophysiol., 1979, 46: 51/)-52/I. Gotman, J., lves, J.R. and Gloor, P. Frequency content of EEG and EKG at seizure onset: possibility of removal of EKG artefact by digital filtering. Electroenceph. clin. Neurophysiol., 1981, 52: 626-639. Gotman, J., lves, J.R. and Gloor, P. (Eds.). D,mg-Term Monitoring in Epilepsy. Supplement 37 to Electroencephalography and Clinical Neurophysiology. Elsevier, Amsterdam, 1985a: 444 pp. Gotman, J., Ives, J.R., Gloor, P., Quesney, L.F. and Bergsma, P. Monitoring at the Montreal Neurological Institute. In: J. Gotman, J.R. Ives and P. Gloor (Eds.), Long-Term Monitoring in Epilepsy (EEG Suppl. No. 37). Elsevier, Amsterdam, 1985b: 327-340. Guedes de Oliveira, P.H.H. and Lopes da Silva, F.H. A topographic display of epileptiform transients based on a statistical approach. Electroenceph. clin. Neurophysiol., 1980, 48: 71/)-714.

DESIGN PRINCIPLES F O R C O M P U T E R I Z E D M O N I T O R I N G Ives, J.R., Thompson, C.J. and Gloor, P. Seizure monitoring: a new tool in electroencephalography. Electroenceph. clin. Neurophysiol., 1976, 41: 422-427. lves, J.R., Mainwaring, N.R., Gruber, L.J., Cosgrove, G.R., Blume, H.W. and Schomer, D.L. 128-Channel cable-telemetry E E G recording system for long-term invasive monitoring. Electroenceph. clin. Neurophysiol.~ 1991, 79:69 72. Jacobs, K.C., Collura, T.F. and Burgess, R.C. Laser printer output of E E G waveforms. J. Clin. Neurophysiol., 1989, 6: 367. Jacobs, E.C., Burgess, R.C. and Collura, T.F. Ergonomic factors of systems for hardcopy and display of EEG. Electroenceph. clin. Neurophysiol., 1991a, 79: 31P. Jacobs, E.C., Burgess, R.C., Collura. T.F., Gotman, J., Lagerlund, T.D., Lesser, R.P. and Webber, W.R. E E G digitalization format for storage and inter lab transmission. In: J. Liiders (Ed.), Surgery of Epilepsy. Raven Press, New York, 1991b. Kaplan, P.W. lind Lesser, R.P, Long-term monitoring. In: T.A, Pedley, D.D. Daly and G. Chatrian (Eds.), Current Practice of Clinical LEG, 2nd Edition. Raven Press, New York, 1990b: 513 534. Kellaway, P. and Frost, Jr., J.D. Monitoring at the Baylor College of Medicine, Houston. In: J. Gotman, J.R. Ives and P. Gloor (Eds.), Long-Term Monitoring in Epilepsy (EEG Suppl. No. 37). Elsevier, Amsterdam, 1985:4113 414. Lesser, R.P., Webber. W.R.S.. Wilson, K. and Fisher, R.S. A microprocessor-based epilepsy monitoring unit. Neurology, 19911, 411 (Suppl. 11: 255. Lopes da Silva, F.tt., Van Hulten, K., Lommen, J.G., Storm van Leeuwen, W., Van Veelen, C.W.M. and Vliegenthart, W. Automatic detection lind localization of epileptic loci. Electroenceph. clin. Neurophysiol., 1977, 43: 1-13, Lopes da Silva, F.H., Storm van Leeuwen, W. and Rdmond, A. (Eds.). Clinical Applications of Computer Analysis of LEG and Other Neurophysiological Signals. Handbook of Electroencephalography and Clinical Neurophysiology, Revised Series Vol. 2. Elsevier, Amsterdam, 1986:5118 pp. Murro, A.M., King, D.W., Smith, J.R., Gallagher, B.B., Ftanigin, tI.F. lind Meador, K. Computerized seizure detection of complex partial seizures. Electroenceph. olin. Neurophysiol., 1991, 79: 3311 333. Nuwer, M.R. Uses and abuses of brain mapping. Arch. Neurol., 1989, 46:1134-1136. Nuwer, M.R.. Engel, Jr., J., Sutherling, W.W. and Babb, T.L. Monitoring lit the University of California, Los Angeles. In: J. Got-

247 man, J.R. Ives and P. Gloor (Eds.), Long-Term Monitoring in Epilepsy (LEG Suppl. No. 37). Elsevier, Amsterdam, 1985:385 401. Nuwer, M.R., Jordan, S.E. and Ahn, S.S. Ewduation of stroke using LEG frequency analysis and topographic mapping. Neurology, 1987, 37: 1153-1159. Oken, B.S. and Chiappa, K.H. Statistical issues concerning computerized analysis of brainwave topography. Ann. Neurol.. 1986, 19: 493 -494. Oken, B.S., Chiappa, K.H. and Salinsky, M. ('omputerized EF, G frequency analysis: sensitivity and specificity in patients with focal lesions. Neurology, 1989, 39:1281 1287. Ozdamar, (-:1,. Yayla[i, 1., Javakar P. lind Lopez, C.N. Multilevel neuronal network system for LEG spike detection. Computerbased medical systems. In: Proc. 4lh Annual lEEK Symposium. Los Alamitos, CA. 1LEE Computer Society Press, 1991: 264-271. Panych, L.P. and Wada, J.A. Computer applications in data analysis. In: J.A Wada and R.J. EIlingson (Eds.), Clinical Neurophysio[ogy of Epilepsy. Handbook of Electroenceph. c[in. Neurophysiol. Revised Series Vol. 4. Elsevier, Amsterdam, 1990: 361-385. Penry, J.K., Porter, R.J. and Dreifuss, F.E. Simultaneous recording of absencc seizures with video tape and electroencephalography. Brain, 1975, 98:427 440. Rdmond, A. The importance of topographic data in tT,EG phenomena lind an electrical model to rcporduce them. Electroenceph. clin. Neurophysiol. (Suppl.), 19611, 27: 29-49. Sato, S., Long, R.L. and Porter, R.J. Monitoring lit the National Institute of Neurological and Communicative Disorders and Stroke. In: J. Gotman, J.R. lves and P. GIoor (Eds.), Long-Term Monitoring in Epilepsy (EEG Suppl. No. 37). Elsevier, Amsterdam, 1985:415 422. Smith, J.R., Funke, W.F., Yeo, W.('. and Ambnchl, R.A. Detection of h u m a n sleep waveforms. Electroenceph. clin. Neurophysiol., 1975, 38: 435-437. Walter, W.G. and Shipton, H.W. A new toposcopic display systcm. Elect roenceph, clin. Neurophysiol., 1951, 3: 281-292. Webber, W.R.S., Wilson, K. and Lesser, R.P. A file system for computer-based LEG. Epilepsia, 1989, 30: 739. Wilson, K., Webber, W.R.S., Lesser, R.P., Fisher, R.S., Eberhart, R.C. and Dobbins. R.W. Detection of epileptiform spikes in the LEG using a patient-independent neural network. In: Computer-Based Medical Systems. Proc. 4th Annual IEEE Symposium, Los Alamitos, CA. lEEK Computer Society Press, 1~191: 264-271.