Detection of bed-exit events using a new wireless bed monitoring assistance

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Abstract

Objectives

To assess, using complete polysomnography as the gold standard, the capability of Heasys®, an innovative wireless bed monitoring assistance to record body movements and presence and to infer bed-exit events and body position changes at night.

Settings

Sleep laboratory for patient's recording and home for healthy volunteers.

Participants

Twelve patients referred for suspicion or treatment of sleep disordered breathing and 5 healthy subjects.

Measurements

Complete polysomnography was recorded during one night in patients and during two nights in healthy volunteers. Heasys® sheet was placed under the fitted bed sheet to allow concomitant recording. During the second night, healthy subjects were asked to get out of bed at least 2 times for a minimal duration of 3 min.

Results

Heasys® allowed the detection of all bed-exit events in patients and volunteers (sensitivity: 100%, and specificity: 85%). When bed-exit events were defined by the lack of the presence signal combined with absence of motion and a dip in temperature, sensitivity and specificity of Heasys® were 92 and 100%, respectively. In patients and volunteers, Heasys® detected body position changes recorded by polysomnography respectively, in 84 and 98% of the cases. Additional recorded motions were mainly related to leg movements or arousals.

Conclusion

In this small feasibility study, Heasys® seemed to be an effective innovative device allowing bed-exit events detection in adult patients and healthy volunteers.

Introduction

In Belgium, as in many developed countries, the geriatric population is constantly increasing. In 2005, 17.2% of the population was older than 65 years and 1.6% older than 85 years. Among them, respectively 8 and 42% were living in nursing home residence. During the next 10 years, the Belgian population above 85 is expected to grow from 180,000 to 285,000, for a total population that will exceed by a small amount 10 millions [1]. With regard to the statistics of nursing home residents, they were 120,000 in 2001 [2] and already 150,000 in 2004 [1], located in 1771 residences.

Nursing care in nursing home residents remains a challenge, in particular during the night when nursing staff is reduced. Repeated physical staff care interventions in order to monitor incontinence, bed egress or behaviour troubles can also result, through repeated awakenings of the residents, into increased sleep fragmentation, sleep disruption and poor quality sleep [3], [4]. These repeated interventions also require a lot of work performed mainly by the nursing staff [5], [6].

Assistive technology is likely to increase in nursing homes in the future and bed-exit alarms have been developed in order to prevent falls that occur mainly in resident's room [7], [8]. Even if only 3–10% of these falls produce serious injury [9], it results in an important negative impact on patient health, functional status and quality of life; and leads to increased health-care costs [10]. Despite the large offer of commercially devices to increase staff surveillance, few well-conducted studies focused on alarm-effectiveness alone in fall prevention and the evidence to support the use of these devices remains limited [8], [11], [12]. Some data however suggest that the performance of multiple sensors may exceed that of single sensors [11].

With this in mind, we have conducted a feasibility study using a new flat bed multi-sensor monitoring equipment (Heasys®, BF Engineering and Datatrak, Brussels, Belgium). Heasys® has been developed to detect the presence of subjects in bed as well as body movements, and allow also the measure of body temperature and urine saturation. The purpose of the present study was to assess whether Heasys® was efficient to detect bed egresses, and if the detection of movements by Heasys® effectively corresponds to body position changes and is influenced or not by other nocturnal events such as arousals and/or leg/foot movements. For this purpose, healthy volunteers but also patients from a general sleep laboratory population were recorded during sleep; these patients were chosen because arousals and/or leg/foot movements are increased in sleep disorders such as obstructive sleep apnea syndrome (OSA) or periodic leg movements during sleep (PLMS) that are common in older subjects [13]. As the reference test for assessing Heasys® data, we used the current standard for the study of sleep and diagnosis of sleep disorders, namely complete polysomnography (PSG) whose measurements made simultaneously can indicate sleep stages/wake periods, body position and leg muscle electromyogram [14].

Section snippets

Patients and normal subjects

During a one-year period, wireless bed monitoring recording was added at random to full night attended PSG in patients referred to Saint-Pierre University Hospital sleep laboratory for suspicion of sleep disordered breathing (SDB) or manual continuous positive airway pressure (CPAP) titration for known OSA. The only prerequisite was patient acceptance, age > 18 and the presence in the sleep laboratory of a technician that had acquired expertise with this new equipment.

Heasys® was also tested at

Results

Five normal subjects (1 man, 4 women) and 12 patients (9 men, 3 women) were studied.

Mean age was respectively 37 + 9 and 45 + 11 years. Indication for sleep recording in patients was OSA suspicion for 10, and CPAP titration for 2. In 3 patients, sleep was considered normal and in 7, OSA diagnosis was reached using PSG (mean apnoea–hypopnea index: 51 + 24). PLMS were recorded in 2 patients using CPAP therapy, in 5 OSA patients and in 2 additional patients.

In healthy subjects, PLMS was recorded during

Discussion

The findings were that Heasys® seems to be a very good tool allowing presence assessment in bed as well as measurement of body motions in normal volunteers and patients referred to a sleep laboratory. All the bed-exit events were associated with a lack of signal from the presence detector. On the opposite, the presence detector suggested some false absence but this was easily corrected using combined analysis based on the lack of signals from presence and motion detectors together with a

Author's contribution

Drs Ninane and Dr Bruyneel have worked together to elaborate the design of the study and to write the manuscript. Data collection and analyses were performed by Mr Libert and Dr Bruyneel.

Conflict of interest statement

All the authors (Dr Marie BRUYNEEL, Mr Walter LIBERT and Dr Vincent NINANE) have disclosed any source of conflict of interest.

Acknowledgements

We acknowledge Mr. J.M. Deleers and Mr. A. Maus (Datatrak Company, Brussels, Belgium) for their precious collaboration.

Summary points

What was already known on the topic:

  • Assistive technology can improve nursing care in nursing home residents.

What this study added to our knowledge:

  • Heasys® seems to be an effective innovative device allowing bed-exit events detection in adult patients and healthy volunteers.

References (21)

There are more references available in the full text version of this article.

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