Sleep Number® Labs, San Jose, CA 95113, USA.
Sensors (Basel). 2022 Mar 29;22(7):2605. doi: 10.3390/s22072605.
The Sleep Number smart bed uses embedded ballistocardiography, together with network connectivity, signal processing, and machine learning, to detect heart rate (HR), breathing rate (BR), and sleep vs. wake states. This study evaluated the performance of the smart bed relative to polysomnography (PSG) in estimating epoch-by-epoch HR, BR, sleep vs. wake, mean overnight HR and BR, and summary sleep variables. Forty-five participants (aged 22-64 years; 55% women) slept one night on the smart bed with standard PSG. Smart bed data were compared to PSG by Bland-Altman analysis and Pearson correlation for epoch-by-epoch HR and epoch-by-epoch BR. Agreement in sleep vs. wake classification was quantified using Cohen's kappa, ROC analysis, sensitivity, specificity, accuracy, and precision. Epoch-by-epoch HR and BR were highly correlated with PSG (HR: r = 0.81, |bias| = 0.23 beats/min; BR: r = 0.71, |bias| = 0.08 breaths/min), as were estimations of mean overnight HR and BR (HR: r = 0.94, |bias| = 0.15 beats/min; BR: r = 0.96, |bias| = 0.09 breaths/min). Calculated agreement for sleep vs. wake detection included kappa (prevalence and bias-adjusted) = 0.74 ± 0.11, AUC = 0.86, sensitivity = 0.94 ± 0.05, specificity = 0.48 ± 0.18, accuracy = 0.86 ± 0.11, and precision = 0.90 ± 0.06. For all-night summary variables, agreement was moderate to strong. Overall, the findings suggest that the Sleep Number smart bed may provide reliable metrics to unobtrusively characterize human sleep under real life-conditions.
睡眠号智能床使用嵌入式心冲击描记术，结合网络连接、信号处理和机器学习，来检测心率（HR）、呼吸率（BR）和睡眠与清醒状态。本研究评估了智能床相对于多导睡眠图（PSG）在逐时估计 HR、BR、睡眠与清醒、整夜平均 HR 和 BR 以及总结性睡眠变量方面的性能。45 名参与者（年龄 22-64 岁；55%为女性）在智能床上睡了一夜，并进行了标准 PSG 检测。通过 Bland-Altman 分析和 Pearson 相关性分析比较了智能床数据和 PSG 数据在逐时 HR 和逐时 BR 方面的差异。使用 Cohen's kappa、ROC 分析、敏感性、特异性、准确性和精密度来量化睡眠与清醒分类的一致性。逐时 HR 和 BR 与 PSG 高度相关（HR：r = 0.81，|偏倚| = 0.23 次/分；BR：r = 0.71，|偏倚| = 0.08 次/分），整夜平均 HR 和 BR 的估计值也高度相关（HR：r = 0.94，|偏倚| = 0.15 次/分；BR：r = 0.96，|偏倚| = 0.09 次/分）。睡眠与清醒检测的计算一致性包括 kappa（流行率和偏倚调整）= 0.74 ± 0.11、AUC = 0.86、敏感性 = 0.94 ± 0.05、特异性 = 0.48 ± 0.18、准确性 = 0.86 ± 0.11 和精密度 = 0.90 ± 0.06。对于所有夜间总结变量，一致性为中度到高度。总体而言，研究结果表明，睡眠号智能床可以在真实生活条件下提供可靠的指标来非侵入性地描述人类睡眠。
