In recent years, ubiquitous computing technolo-gies have been applied in the field of medicine.Especially radio frequency identification (RFID)and small sensor networks could provide informa-tion about medical practices and patient status inorder to prevent malpractices and improve thequality of medical care. As an example of this appli-cation, we developed a new system, named ““asmart stretcher,”” which continuously monitors thepatient’’s vital signs and detects apnea duringtransfer within a hospital. This system consists of asmall air-mat type pressure sensor measuringboth heart rate and respiration rate and a wirelessnetwork transmitting these vital data as well aspatient ID to an alerting system to notify hospitalstaff of patient emergencies. Results of experi-ments in a clinical setting indicated that the systemwas reliable in continuous respiration monitoringand detection of apnea during patient transfer onthe stretcher; however, detection of heartbeat ratewas practically difficult because of the motionnoises. Moreover patient ID and location werealso correctly detected in real time. These resultssuggested the feasibility of our system for real clin-ical use.

Key words: Medical errors, Patient monitoring,Safety of medical care, WirelessLocation detection, RFID

Introduction

Advances in ubiquitous communication technolo-gies, such as radio frequency identification (RFID)and small sensor networks, are giving rise to new appli-cations in the various fields. In the medical field, espe-cially in hospitals, these ubiquitous communicationtechnologies can improve the safety of medical treat-ment in order to prevent malpractice1 and improve thequality of medical care.2-4

Various measures to prevent medical errors byusing checklist or repetition of the orders have been putin place already,5 but medical errors cannot be elimi-nated by human effort alone. The utilization of ubiqui-tous communication technology is expected to cover“non-computerized gaps” in medical practice whereconventional hospital information systems have notbeen sufficiently effective.

The application of ubiquitous communication tech-nologies in medicine ultimately aims to realize an“intelligent environment” 6 within the hospital, in whichthe physiological status and behavior of patients arecontinuously monitored in order to provide the bestmedical care at any time and at any location within thehospital, with security and safety.

As an example of an intelligent hospital environment,we focused on emergency management duringpatient transfer in hospital. In operating rooms, emer-

Original Article

Safe patient transfer system with monitoring of location and vital signs

Kumiko Ohashi1, Yosuke Kurihara2, Kajiro Watanabe3 and Hiroshi Tanaka4

1) Department of Bioinformatics, Tokyo Medical and Dental University Graduate School, Japan2) Graduate School of Engineering, Hosei University3) Faculty of Engineering, Hosei University4) Tokyo Medical and Dental University Center for Information Medicine, Japan

J Med Dent Sci 2008; 55: 33–41

Corresponding Author: Kumiko Ohashi1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8549 JapanTelephone number: 81-3-5803-4673E-mail address: ohashi@bioinfo.tmd.ac.jpReceived October 2; Accepted November 30, 2007

gency rooms, intensive-care unit (ICU) or in somecases, even in ordinary wards, patients can be readilymonitored for changes in vital signs, but during theirtransfer, the physiological status of patients is often notmonitored. This may result in medical accidents.Monitoring of respiration is one of the crucial aspects inmedical treatment.

In this study, we developed a new wireless systemnamed “a smart stretcher,” which continuously monitorsthe patient’s vital signs and detects apnea duringtransfer within a hospital. The main purpose of the sys-tem is to prevent medical errors such as the accidentaloverlooking of patient emergency status and misiden-tifications of patients. Especially, we focused on alertingpatients’ apnea to medical staff while the patient isbeing transferred within the hospital.

The monitoring system consists of an air-mat typesupersensitive pressure sensor measuring heart rateand respiration rate and an ad hoc wireless communi-cation ZigBee network that transmits these vital data tothe hospital LAN and to an alerting system to notifyhospital staff in case of an emergency. The patient’s ID,read from an RFID wristband, is also transmitted to thealerting system to prevent misidentification of thepatient.

We conducted experiments to estimate the feasibili-ty of this wireless monitoring system in a real clinical sit-uation. Our goal was to examine whether the system

could detect apnea during patient transfer on astretcher within the hospital.

System Description

Main components of the smart stretcher systemThree measurement devices are incorporated in

the stretcher: the first device measures vital signs, suchas heart and respiration rate for detecting apnea; thesecond provides automatic patient ID recognition; andthe third detects patient location within the hospital.

The three kinds of patient information provided bythese three devices are transmitted by a wireless net-work system incorporated in the stretcher, implement-ed with ZigBee. The ZigBee signals of the patient’s vitalsigns emitted from the stretcher’s monitoring systemare received by ZigBee routers distributed within thehospital (e.g., on corridor ceilings). The routers com-municate with each other to form an ad hoc network, anode of which is connected to a PC that serves as agateway to the hospital information system.

The measurement devices work together to monitorthe patient’s physiological status, and when an emer-gency such as apnea is detected, information about theemergency is transmitted to the alerting system in theward (Fig. 1).

K. OHASHI et al. J Med Dent Sci34

Fig. 1. System configuration of the smart stretcher

Vital sign-monitoring systemThe vital sign-monitoring system incorporated in

the smart stretcher continuously measures the minutevibrations of the patient’s body by means of a super-sensitive air-mat type sensor and decomposes thesesignals into respiration frequency and heartbeat fre-quency components. This air-mat type sensor hasalready demonstrated its validity and precision indetecting respiration rate and heartbeat7. To makesure the validity of the air-mat type sensor measure-ment during the transfer of the stretcher, we comparedthe respiration and heartbeat signal measured by theair-mat type with that of a strain sensor for respirationrate and that of a pulse oximeter for heart rate.

The vibration signals thus measured by the air-mattype sensor were analyzed with a fast fourier transform(FFT) analysis, which decomposes the temporalvibration signals into sum of the oscillatory componentshaving various frequencies, then the frequency com-ponents corresponding to heartbeat and respiration ratewere filtered out respectively.

The results of the measurements of both respirationand heart rate are transmitted every 15 s through theZigBee wireless node in the stretcher. The data are dis-played on the computer screen of the medical terminal

in the ward. The apnea warning system is included inthis monitoring system.

Apnea warning systemThe apnea-warning algorithm was developed to

detect respiratory arrest when the amplitude of the res-piratory waveform falls below a predetermined thresh-old from a moving baseline, temporally averaged overthe last five sampling points.

When it detects apnea, the system transmits awarning signal to the monitoring system of thestretcher, the nurse’s PDA, and terminals in the hospi-tal information system. Thus, not only does the moni-toring system of the stretcher emits an apnea warning,but it also simultaneously sends alerts to the nurse’sPDA and the nurse station PCs in the ward. An exam-ple of the screen display of a nurse’s PDA is shown inFig. 2. The patient’s name, measurement time, respi-ratory rate, heart rate, and respiratory state are dis-played at 15-s intervals. When apnea is detected, a redwarning display appears and the system emits awarning alarm. The nurse who is transferring thepatient recognizes the need for emergency carebased on these warnings and calls the patient’s doctorimmediately.

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Fig. 2. Screenshot of the nurse’s PDA

Automatic patient ID recognition systemThe patient’s ID information is stored in the RFID tag

incorporated in the left wristband, and an RFID readeris located on the left side of the stretcher, which recog-nizes the patient ID automatically. Other patient infor-mation is not directly stored in the RFID tag, but isretrieved from the database using the tag’s UID(unique ID peculiar to the tag).

The RFID reader starts the process of reading thepatient’s ID when the “bed-leaving” sensor attached tothe stretcher detects that a patient is on board thestretcher. The RFID reader is connected to theZigBee network. If the patient’s ID data are successfullydetected, the RFID reading system emits one beep. If areading error occurs, such as when no ID information isdetected or if two or more different patient IDs are readwithin a given period, the system emits a continuousbeep tone. The RFID reader uses the polling mode,whereby the data of a tag are read only within a fixedperiod, usually set to 30 s. If the reader fails to detectthe patient’s ID, it retries to read it for another 30 s.

Location detection system using the ZigBee net-work

To detect the location of the patient and stretcher in

real time and to pass this information to other medicalstaff in the event of a patient emergency, a locationdetection system is integrated with the ad hoc ZigBeenetwork within the hospital. A received signal strengthindicator (RSSI) system is used, which estimates thelocation according to the signal intensity received by thedistributed ZigBee location routers in the hospital cor-ridors. The ZigBee wireless tag attached to thestretcher transmits a unique ID and wireless signal to allZigBee location routers at 10-s intervals.

Each ZigBee router has a known location. Each ofthe routers receives the signals from the ZigBee nodeof the stretcher and transmits the node tag IDattached to the stretcher, and the intensity of the signalreceived from the ZigBee node, together with its ownZigBee router ID, to the ZigBee gateway and the hos-pital LAN. The patient’s location is estimated by identi-fying the ZigBee router that has the greatest signalintensity. The ZigBee routers constitute an ad hoc meshnetwork that transmits location information reliably tothe gateway (Fig. 3).

K. OHASHI et al. J Med Dent Sci36

Fig. 3. The ZigBee mesh network for detecting the location of the patient on the stretcher

Clinical feasibility experiment

We conducted a feasibility experiment with thesmart stretcher in an actual clinical setting. In the exper-iment, three subjects, two males and one female,each took the role of a patient being transferred on thestretcher. First, the subjects lay down on the smartstretcher at an angle of 45 degrees and wore a strainsensor on their abdomens and a pulse oximeter ontheir ear lobes for obtaining respiration and heartbeatreference signals. Also, they wore an RFID wristbandon their left hands for identification recognition.

Second, the readability of the wristband patient IDwas examined. The distance at which the patientwristband ID could be recognized by the RFID readerlocated on the left side of the stretcher was measured.The RFID system used and the experiment environ-ment are shown in Fig. 4. We changed the reading con-ditions, such as the types of tag, positions of the RFIDreader antenna, and posture of patients, and in eachcase, we measured the maximum readable distancesfrom the reader antenna installed on the left side of thestretcher. Third, the subject on the stretcher wastransported at a speed of 4.5km/hr, and was asked tostop breathing intentionally in the meantime to investi-

gate whether the monitoring system would detect theapnea in spite of the movement of the stretcher andwould emit a warning signal. We measured apneatimes of three subjects by using the smart stretcher’ssensor and a strain sensor. For the setting, of theexperiment we installed five ZigBee routers and onegateway located at regular intervals on the ceiling of ahospital corridor. Two members of the hospital staff car-ried the subject on the smart stretcher in the hospitalcorridor for 80 m. We monitored patient location on thefloor map display of the terminal connected to theZigBee network.

Results

Readability of Patient IDIn almost all cases, the RFID was recognized within

15 s after the reader started and the patient ID was dis-played on the monitoring screen in real time.Readable distances from the RFID antenna (left side ofthe stretcher and under the mat) are shown in Table I.Mat thickness was 55 mm. The readable distance lim-its for patient ID increased in proportion to tag size.There was no difference in readable distance

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Fig. 4. The experiment to verify the automatic patient ID recognition system

between the patient positions of face-up and semi-sit-ting. The readable distance of the RFID reader placedon the left side of the stretcher was much better thanwhen it was under the mat (Table I). Identification wasmost reliable when the patient’s hand wearing the RFIDwristband was positioned straight along the edge line ofthe stretcher; identification was difficult when thehand was not in that position. When two IDs were readat the same time, the patient ID was displayed as“unknown” and the system emitted a beep to alert med-

ical staff of the need for re-reading.

Detection of ApneaReliable measurements were obtained for respiration

rate during transfer for each of the three subjects. Oneof the measurement results is shown in Fig. 5. Heartrate frequency is within 0.5-2 Hz and respiration rate iswithin 0.1-0.5 Hz in a normal subject. The result of anFFT analysis of the data in Fig.5 is shown in Fig. 6. Thepeaks of respiration frequency were within 0.1-0.5 Hz inall subjects. In all cases, heart rate frequency wasmostly within 0.5-2 Hz, but the results had a few highpeaks in the frequency spectrum that were thought tobe caused by motion noise during the movement of thestretcher. The measured respiration waveforms indi-cated the apnea by flattening out for about 10 s.

The respiration signals corresponded with the spec-trum of respiration by reference. However, the spectrumof heartbeat did not correspond with the highest peakof the spectrum but second higher spectrum. Webelieve that these results occurred due to the stretch-er’s movement noise. However, we confirmed that therespiration rate could be correctly detected by thevital-monitoring system although heartbeat rate couldnot obtained in this setting.

K. OHASHI et al. J Med Dent Sci38

Fig. 5. The measurement results during the smart stretcher’s transfer

Table I The results of readable distances of patient ID

The apnea detection method worked well as shownin an example of the respiratory waveforms for detect-ing apnea during transfer in Fig. 7. The measured res-piration waveforms indicated the apnea by flattening outfor about 10 s. By referencing the waveform of thestrain sensor, it was considered that the apnea-warningalgorithm could effectively detect correct apnea time.

We measured the detection rate for apnea by thesmart stretcher. The results are summarized in Table II.The apnea of subject A and B were almost completelydetected. However, that of subject C was detected at77.1% because of motion noise that raised the respi-ratory signal higher than the threshold consequently,and as a result it was regarded that the subject was

39SAFE PATIENT TRANSFER SYSTEM

Fig. 6. The results of FFT analysis of fig 5 data

Fig. 7. The respiratory waveforms for detecting apnea during a transfer

breathing. Overall, apnea could be detected at the rateof 99.1% on average with all subjects. Moreoverthrough the ZigBee wireless network, the patient’sname, respiration rate, and heart rate were correctlydisplayed on the PDA screen. The apnea warning alertand the warning screen on the PDA were also dis-played almost in real time.

Detection of Location of the Smart StretcherThe location detection system showed good perfor-

mance in providing the correct location in real time (Fig.8). Radial distance of detecting location was 15 m. Therange of error was ±10 m. Serious errors and delays inthe display of the detected location were not observedin this location detection experiment.

Discussion

From these preliminary results, the patient’s vitalsigns, ID, and location could be obtained in real timeduring transfer of a patient on the smart stretcher.Using three kinds of information, the smart stretchermay be able to contribute to medical safety, especiallythe oversight of the patient’s physical status, preventionof misidentification of patient, and miscommunicationwith other medical staff in the clinical setting.

There are some previous studies of the use of RFIDfor preventing errors in medication8 and in the identifi-cation of patients and medical staff.9 However, otherthan a study using a location detection system, thesestudies have concerned only patient’s rooms or opera-tion rooms.10-12 Medical errors can occur at any place ina hospital. The stretcher system described here can be

K. OHASHI et al. J Med Dent Sci40

Fig. 8. Screenshot of the location detection application (PC screen)PC: Dell (PP21L, OS: windows XP, Memory: 512Mbyte)

Table II The detection rate of apnea

used irrespective of the location of the patient.Moreover, it monitors the patient’s state automaticallywithout the need for staff to attach medical devices tothe patient. However, measurements were some-times less precise because of various environmentalfactors. Nevertheless, the smart stretcher system hasthe advantage of being able to use easily withoutattaching any sensors to patients for monitoring theirvital signs and transmit the data in real time. The phys-iological status and behavior of patients are constantlymonitored to facilitate safe medical care anytime, any-where in the hospital. We need further detailed investi-gation of the factors that influence the precision of themeasurements to improve the recognition perfor-mance of RFID and the measurement of vital signs.

With regard to the results of location detection, indi-vidual stretcher locations were not detected accuratelybecause the location error was about 10 m. We thinkthat accuracy can be increased by adjusting the systemsettings to fit the specific hospital environment where itis being used.

This system demonstrates the feasibility of usingwidely used technology as part of a preventive measurefor medical malpractice. However, it is somewhat diffi-cult to use this system in clinical practice as it is,because of problems such as cost, system operation,and network infrastructure. We consider that thisstudy is another step toward realizing a smart medicalspace with security and safety.

Acknowledgments

This study was performed with the help of SpecialCoordination Funds for Promoting Science andTechnology of the Ministry of Education, Culture,Sports, Science and Technology, Japanese. Wewould like to acknowledge Hitachi, Ltd., Uniadex

Corporation and Jepico Corporation for their collabo-ration in the development of the vital signs monitoringsystem.

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