收藏切换
Application effect of a non-contact sleep monitoring mattress based on body movement characteristics during sleep
收藏切换
Yanchun ZHANG, Yan LIU, Rui WANG, Feilong WANG, Yue ZHAO, Fei LI, Tunan CHEN, Jishu XIAN
Journal of Army Medical University | 2025, 47(4) : 326 - 334
Less
收藏切换
Journal of Army Medical University | 2025, 47(4): 326-334
• Monographic Reports •
Application effect of a non-contact sleep monitoring mattress based on body movement characteristics during sleep
Full
Yanchun ZHANG, Yan LIU, Rui WANG, Feilong WANG, Yue ZHAO, Fei LI, Tunan CHEN, Jishu XIAN
Affiliations
  • 1Department of Neurosurgery,First Affiliated Hospital,Army Medical University (Third Military Medical University),Chongqing,China
Published: 2025-02-28 doi: 10.16016/j.2097-0927.202410073
Outline
收藏切换
Objective

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.

Methods

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.

Results

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.

Conclusion

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.

sleep disorder  /  wearable devices  /  inpatients  /  nursing assessment
张燕春, 刘艳, 汪睿, 王飞龙, 赵悦, 李飞, 陈图南, 鲜继淑. 基于睡眠期体动特征的无感睡眠监测床垫的应用效果评价. 陆军军医大学学报, 2025 , 47 (4) : 326 -334 . DOI: 10.16016/j.2097-0927.202410073
Yanchun ZHANG, Yan LIU, Rui WANG, Feilong WANG, Yue ZHAO, Fei LI, Tunan CHEN, Jishu XIAN. Application effect of a non-contact sleep monitoring mattress based on body movement characteristics during sleep[J]. Journal of Army Medical University, 2025 , 47 (4) : 326 -334 . DOI: 10.16016/j.2097-0927.202410073
Year 2025 volume 47 Issue 4
37
16
Cite this Article
BibTeX
Article Info
doi: 10.16016/j.2097-0927.202410073
  • Receive Date:2024-10-21
  • Online Date:2026-10-30
  • Published:2025-02-28
Article Data
Affiliations
History
  • Received:2024-10-21
  • Revised:2024-11-18
Affiliations
    1Department of Neurosurgery,First Affiliated Hospital,Army Medical University (Third Military Medical University),Chongqing,China
References
Share
https://castjournals.cast.org.cn/joweb/ljjydxxb/EN/10.16016/j.2097-0927.202410073
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT