Application effect of a non-contact sleep monitoring mattress based on body movement characteristics during sleep

To verify the accuracy of a Non-Contact Sleep Monitoring Mattress(NCSMM based on body movement during sleep in assessing sleep quality of patients before neurosurgery in order to provide a more portable and efficient assessment tool for clinical staff.

A single-arm trial was conducted on 114 inpatients admitted in our department selected with convenience sampling. Sleep quality data of 1 night were collected through 5 sleep quality assessment tools, including NCSMM, polysomnography（PSG）, Patient-Reported Outcome Measurement Information System（PROMIS） Sleep Disturbance scale,Richards-Campbell Sleep Scale（RCSQ）, and a wearable device（smart watch for body movements and sleep quality monitoring）. The sleep efficiency（≤85%） obtained by PSG was used as the diagnostic standard for sleep disorders. The area under the receiver operating characteristic curve（AUC）, sensitivity, specificity,positive predictive value, negative predictive value, and Youden index were calculated for the other 4 tools to evaluate and compare their diagnostic effectiveness.

The AUC value for NCSMM, PROMIS, RCSQ and smart watch was 0. 788（95%CI: 0. 687～0. 888, P＜0. 001）, 0. 664（95%CI: 0. 543～0. 784, P=0. 02）,0. 723（95%CI: 0. 600～0. 846, P=0. 001） and 0. 750（95%CI: 0. 654～0. 846, P＜0. 001）, respectively. The diagnostic accuracy rate was 0. 774, 0. 559, 0. 742 and 0. 602, with corresponding Youden index value of 0. 488, 0. 321, 0. 456, and 0. 459. NCSMM demonstrated the best AUC value, sensitivity and Youden index when compared with the other 3 tools.

NCSMM shows high accuracy in assessing sleep quality in pre-neurosurgery inpatients, and it is a viable portable and efficient assessment tool in clinical practice.