兽研[内容请查看原文]
引言
心率（HR）和外周血氧饱和度（SpO2）是用于评估人类和兽医医学中心血管和呼吸功能的重要生理参数（Cugmas et al. 2019; Yanmaz et al. 2023）。心率是临床评估中的主要指标，常规用于确定疾病预后和评估治疗反应。SpO2是监测患者氧合状态的关键指标（Yanmaz et al. 2023）。
在兽医实践中，心率和SpO2的测量是体格检查、外科手术和重症监护管理的标准组成部分（Bednarski et al. 2011; Cugmas et al. 2019）。这些参数可从多个解剖部位获取，包括舌、耳廓和爪部，并在清醒和麻醉动物中提供有价值的临床信息（Matthews et al. 2003; Cugmas et al. 2019; Dörfelt et al. 2021）。
低氧血症仍然是全球范围内导致死亡的重要原因。监测SpO2能够早期、无创地检测血氧水平下降及潜在的呼吸功能不全的发生（Humm and Kellett‐Gregory 2016; Hasan and Negulescu 2020）。
Owlet Smart Sock（OSS）是一种可穿戴设备，专为监测人类新生儿睡眠期间的心率和SpO2而开发。该系统将医院级无创脉搏血氧饱和度传感器嵌入设计贴合婴儿足部的柔软袜套中。记录的数据通过蓝牙传输至基站，随后通过移动应用程序和云平台传递给用户（Young and Flores 2020; Hasan and Negulescu 2020）。
迄今为止，尚无研究报道OSS在猫中测量心率和SpO2的准确性或临床一致性。因此，本研究旨在评估使用OSS在麻醉猫中获取的心率和SpO2测量值与参考兽医床旁监护仪（监护仪1）相比的准确性和一致性。
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材料与方法
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动物
研究群体包括20只临床健康的混种猫，因常规牙齿清洁就诊于阿塔图尔克大学动物医院。动物年龄在1至2岁之间，体重范围为3.2至5.1 kg。
入组前，所有猫均接受了全面的体格检查和常规血液学检测。身体状况根据美国麻醉医师协会（ASA）标准进行分类，仅将归类为ASA I的猫纳入研究。
研究方案经阿塔图尔克大学动物实验地方伦理委员会批准（决定号：2026/02）。已获得所有主人的书面知情同意。术前禁食6小时，麻醉前禁水2小时。
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麻醉前给药与麻醉
对所有猫实施标准化麻醉方案。麻醉前给药包括曲马多（2 mg/kg，肌肉注射）和右美托咪定（0.08 mg/kg，肌肉注射）。使用丙泊酚（4 mg/kg，静脉注射）诱导麻醉。麻醉前给药后，在头静脉放置静脉导管以进行液体支持，整个操作过程中以3 mL/kg/h的维持速率给予0.9% NaCl溶液。丙泊酚诱导和气管插管后，使用七氟烷在100%氧气中维持麻醉，根据临床麻醉深度将蒸发器设置调整在1.5%至2.5%之间。
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测量设备与应用
对于心率和SpO2评估，使用兽医患者监护仪（监护仪1；Cardell 9405，Sharn Veterinary Inc.，佛罗里达州坦帕）作为参考方法。
心率使用集成的心电图（ECG）功能测量，而SpO2值则使用监护仪的透射式脉搏血氧饱和度（TPO）传感器置于舌部获取。电极按照制造商的建议放置，导联连接至右前肢、左前肢和左后肢。心率值直接从监护仪显示屏读取。
为验证监护仪1的准确性，同时使用听诊器在30秒窗口内进行手动听诊心率测量，并外推至每分钟心跳次数（bpm）。同时通过计数完整60秒期间的胸廓视觉运动来确定呼吸频率，以确认数据合并前呼吸状态稳定。
OSS（Owlet Smart Sock‐2，Owlet Baby Care Inc.，犹他州莱希，美国）用作可穿戴监测设备。为尽量减少传感器与皮肤之间潜在的光学伪影，使用40号刀片剃除胫部应用部位的毛发。设备放置于胫部区域，未使用额外胶带或绷带。其袜套式设计在应用部位提供了足够的固定（图1）。所有猫均使用OSS 1号尺寸，因为它最适合研究群体的体型和远端肢体周长，确保监测期间传感器定位稳定和皮肤接触一致。
[图：使用OSS获取心率和SpO2测量值的胫骨区域。]
在20分钟的数据采集窗口内，所有猫均保持稳定的右侧卧位于有衬垫的手术台上。OSS统一应用于左侧骨盆肢（非依赖肢），以避免依赖肢可能带来的承重伪影或局部微循环受损。
为便于统计分析和图形展示，OSS被命名为“Device”，而参考兽医患者监护仪（Cardell 9405）被命名为“Monitor 1”。
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数据采集程序
在20分钟期间，以1分钟为间隔同时使用两种设备记录HR和SpO2测量值。数据采集由三名研究者同时进行：一人记录OSS测量值，一人记录从Monitor 1获得的值，一人使用听诊器进行并记录听诊HR测量值。
所有采集的数据均转入电子表格以供后续统计分析。最终分析共纳入307对配对测量值。
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统计分析
所有统计分析均使用MedCalc（v. 20.013，MedCalc Software Ltd，Ostend，Belgium）进行。连续变量以均值±标准差（SD）及相应的95%置信区间（CI）表示。正态分布假设通过目视检查方法和描述性统计进行评估。
设备间的一致性采用Bland–Altman分析评估，计算平均差值（偏倚）和95%一致性界限（均值±1.96 SD）。测量差值与测量幅度之间的关系采用回归分析检验。
临床等效性采用双单侧检验（TOST）程序评估。等效性界值预先设定为HR ±10 bpm，SpO2 ±3%。所有分析中p值<0.05视为具有统计学意义。
设备间的线性关联采用Pearson相关分析，报告相关系数（r）及相应的p值。
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结果
本研究共纳入20只猫。在使用OSS和Monitor 1获得的测量值中，307对HR和SpO2数据点被纳入统计分析。其余数据点因数据采集过程中的同步差异而被排除。最终分析仅纳入完整且时间匹配的测量值。
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心率
OSS与Monitor 1在HR测量值之间呈极强且具有统计学意义的线性相关（r = 0.995，p<0.0001；表1，图2）
TABLE 1. Mean difference (bias), 95% limits of agreement derived from Bland–Altman analysis, and correlation coefficients for HR and SpO 2 measurements between the OSS and Monitor 1.
| Parameters | Mean difference (bias) | Lower limit (%) | Upper limit (%) | Correlation ( r ) | p (r) |
|---|---|---|---|---|---|
| HR | 0.224 | −3.36 | 3.81 | 0.995 | <0.0001 |
| SpO 2 | −0.538 | −4.78 | 3.7 | 0.634 | <0.0001 |
[图：OSS（设备）与监护仪1之间心率测量的相关性分析。]
在比较Monitor 1与OSS的Bland–Altman分析中，计算得出的平均差值为0.224 bpm，具有统计学意义（p = 0.0326）。95%一致性界限范围为−3.36至3.81 bpm（表1；图3）。
[图：OSS与监护仪1之间心率测量的Bland–Altman分析。]
回归分析显示斜率具有统计学意义（p = 0.0011）。
在TOST分析（±10 bpm等效界值）中，平均差值为0.18 bpm（95% CI：−0.38–0.40），表明具有临床等效性（p < 0.0001；表2）。
TABLE 2. Results of the TOST equivalence analysis of HR and SpO 2 measurements between the OSS and Monitor 1.
| Comparison | Mean Difference | 95% CI (bias) | TOST p ‐value | Clinical equivalence |
|---|---|---|---|---|
| HR Monitor 1—Device (bpm) | 0.18 | −0.38–0.40 | <0.0001 | Equivalent |
| SpO 2 Monitor 1—Device (%) | −0.5 | −0.74 to −0.29 | <0.0001 | Equivalent |
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外周血氧饱和度
OSS与Monitor 1在SpO2测量值之间呈具有统计学意义的线性相关（r = 0.634；p < 0.0001；表1；图4）。
[图：OSS与监护仪1之间SpO2测量的相关性分析，包括热图和回归曲线。]
在Bland–Altman分析中，计算得出的平均差值为−0.538 bpm，95%一致性界限范围为−4.78至3.7 bpm（表1；图5）。
[图：OSS与监护仪1之间SpO2测量的Bland–Altman分析。]
在TOST分析（±3%等效界值）中，平均差值为−0.5%（95% CI：−0.74至−0.29），表明具有临床等效性（p < 0.0001；表2）。
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讨论
心率和血氧饱和度是兽医临床实践中评估心肺状态的基本参数。对此类生命体征进行连续、无创监测的兴趣日益增加（Cugmas et al. 2019; Yanmaz et al. 2023）。尤其是在全身麻醉期间，对这些参数的监测对于早期识别麻醉相关并发症至关重要（Li et al. 2015; Tamura et al. 2015; Pypendop et al. 2019; Dörfelt et al. 2022）。与犬相比，猫被认为具有更高的麻醉相关死亡风险（Dörfelt et al. 2022）。因此，评估可靠的监测系统具有重要的临床意义。
近年来，可穿戴技术在兽医医疗保健领域受到越来越多的关注。这些系统具有潜在优势，特别是在心肺参数的无创连续监测方面（Mitek et al. 2022）。基于光电容积脉搏波描记法（PPG）的系统通过光学检测组织血容量的变化来测量心率和血氧饱和度（Cugmas et al. 2019; Hasan and Negulescu 2020）。OSS设备即依据此原理工作（Hasan and Negulescu 2020）。然而，毛发和色素沉着的皮肤可能影响光吸收，从而降低信号质量；因此，建议对测量部位进行剃毛（Cugmas et al. 2019）。在本研究中，设备放置前对胫部区域进行剃毛并在麻醉状态下进行测量，旨在最大限度地减少潜在的光学伪影和运动相关的信号干扰。
在人医领域，已有报道称OSS设备在测量新生儿心率和血氧饱和度方面具有可接受的准确性（Dangerfield et al. 2017）。此外，其用于早期发现一例罕见室性心动过速的案例已有文献记载（Young and Flores 2020）。然而，兽医文献中尚无专门评估OSS在猫中应用的研究；现有出版物主要涉及可穿戴技术的更广泛应用（Mitek et al. 2022）。
在本研究中，对于全身麻醉下健康猫的心率测量，OSS与监护仪1之间观察到极强的线性相关性（r = 0.995；p < 0.0001）。Bland–Altman分析显示平均差异为0.224 bpm，95%一致性界限范围为−3.36至3.81 bpm。平均差异具有统计学意义（p = 0.0326）。在TOST分析中，在预设的±10 bpm等效界值范围内确认了临床等效性（p < 0.0001）。这些结果表明，在受控的麻醉条件下，OSS能够提供与监护仪1一致的心率测量结果。
对于血氧饱和度测量，两种设备之间发现具有统计学意义的线性相关性（r = 0.634；p < 0.0001）。Bland–Altman分析显示平均差异为−0.538 bpm，95%一致性界限范围为−4.78至3.7 bpm。平均差异具有统计学意义。在TOST分析中，在预设的±3%等效界值范围内证明了临床等效性（p < 0.0001）。然而，与心率相比，相关系数较低且一致性界限较宽，提示血氧饱和度测量的变异性较大。
在猫中，心血管疾病如肥厚型心肌病（Kitz et al. 2019; Şahin et al. 2025）、先天性心脏病（Abboud et al. 2025）和动脉血栓栓塞（Kitz et al. 2019; Şahin et al. 2025），以及呼吸系统疾病包括猫哮喘和慢性支气管炎（Chalifoux et al. 2021; Abboud et al. 2025）、各种形式的肺炎（Boiron et al. 2019; Abboud et al. 2025）、急性肺损伤和急性呼吸窘迫综合征（Balakrishnan et al. 2017）、上呼吸道疾病（Chalifoux et al. 2021; Abboud et al. 2025）和胸腔积液（Abboud et al. 2025），可能导致心率和血氧饱和度出现具有临床意义的改变。因此，对这些参数进行可靠监测可能有助于早期发现有心肺疾病风险的猫的临床恶化。然而，本研究的发现仅限于全身麻醉下的健康猫，不应直接外推至患病群体。
本研究存在若干局限性。样本量有限，且仅纳入临床健康、ASA I级的猫。测量在受控条件下于全身麻醉期间进行，运动极少。因此，设备在有意识且活动的猫中的性能可能有所不同。OSS仅在单一解剖部位（胫骨）进行了评估。虽然胫部区域提供了足够的固定，但兽医监测中常规使用的替代部位（如跖骨、趾部或尾根部）未被探索。这些部位在组织厚度和血管分布方面存在差异，可能影响光吸收和PPG信号质量。另一个局限性是未使用灌注指数（PI）客观量化外周灌注。由于右美托咪定可能引起外周血管收缩，外周灌注改变对OSS性能的潜在影响无法被具体评估。
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结论
本研究表明，在全麻状态下的健康猫中，OSS在心率测量方面与参考监测仪表现出高度一致性，并在预定义的等效范围内提供临床可接受的SpO2值。这些发现表明，该设备可能成为一种有用的无创工具，用于在受控麻醉条件下监测心肺参数。然而，由于本研究仅限于健康猫、单一传感器放置部位和受控麻醉条件，仍需开展涉及更大样本量、多样化临床群体、替代解剖部位和不同灌注状态的进一步研究，以确认并扩展这些发现。
作者贡献
Mümin Gökhan Şenocak：方法学、形式分析。Şule Melek：概念化、方法学、监督、写作——审阅与编辑、写作——原始草稿。Ömer Tarık Orhun：概念化、方法学、数据管理、验证。Taner Arslan：数据管理。
资助
本研究由土耳其科学技术研究委员会（TÜBİTAK）资助。
伦理声明
作者确认已遵守期刊作者指南页面所述的期刊伦理政策，并已获得相应的伦理审查委员会批准。研究方案已获阿塔图尔克大学动物实验地方伦理委员会批准（批准号：2026/02）。
利益冲突
作者声明无利益冲突。
致谢
人工智能仅用于语言和语法编辑。所有科学内容和分析均由作者完成。
数据可用性声明
文章数据可应通讯作者要求提供。
参考文献
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关联数据
数据可用性声明
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Introduction
Heart rate (HR) and peripheral oxygen saturation (SpO2) are essential physiological parameters used in the assessment of cardiovascular and respiratory function in both human and veterinary medicine (Cugmas et al. 2019; Yanmaz et al. 2023). HR represents a principal indicator during clinical evaluation and is routinely applied in determining disease prognosis and assessing therapeutic response. SpO2 serves as a critical measure for monitoring a patient's oxygenation status (Yanmaz et al. 2023).
In veterinary practice, the measurement of HR and SpO2 constitutes a standard component of physical examinations, surgical procedures and intensive care management (Bednarski et al. 2011; Cugmas et al. 2019). These parameters can be obtained from various anatomical sites, including the tongue, pinnae and paws and provide valuable clinical information in both conscious and anaesthetised animals (Matthews et al. 2003; Cugmas et al. 2019; Dörfelt et al. 2021).
Hypoxaemia remains a significant cause of mortality worldwide. Monitoring SpO2 enables early, non‐invasive detection of reductions in blood oxygen levels and the potential onset of respiratory insufficiency (Humm and Kellett‐Gregory 2016; Hasan and Negulescu 2020).
The Owlet Smart Sock (OSS) is a wearable device developed to monitor HR and SpO2 in human neonates during sleep. The system incorporates a hospital‐grade, non‐invasive pulse oximetry sensor embedded within a soft sock designed to fit the infant's foot. Recorded data are transmitted via Bluetooth to a base station and subsequently delivered to the user through a mobile application and cloud‐based platform (Young and Flores 2020; Hasan and Negulescu 2020).
To date, no studies have reported on the accuracy or clinical agreement of the OSS for measuring HR and SpO2 in cats. Accordingly, the objective of this study was to evaluate the accuracy and agreement of HR and SpO2 measurements obtained using the OSS in anaesthetised cats, in comparison with a reference veterinary bedside monitor (Monitor 1).
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Materials and Methods
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Animals
The study population consisted of 20 clinically healthy mixed‐breed cats presented to Atatürk University Animal Hospital for routine dental cleaning. The animals were between 1 and 2 years of age, with body weights ranging from 3.2 to 5.1 kg.
Prior to enrolment, all cats underwent a comprehensive physical examination and routine haematological testing. Physical status was classified according to the criteria of the American Society of Anaesthesiologists (ASA), and only cats categorised as ASA I were included in the study.
The study protocol was approved by the Local Ethics Committee for Animal Experiments of Atatürk University (decision no: 2026/02). Written informed consent was obtained from all owners. Preoperatively, food was withheld for 6 h and water for 2 h before anaesthesia.
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Premedication and Anaesthesia
A standardised anaesthetic protocol was implemented in all cats. Premedication consisted of tramadol (2 mg/kg, intramuscularly) and medetomidine (0.08 mg/kg, intramuscularly). Anaesthesia was induced with propofol (4 mg/kg, intravenously). Following premedication, an intravenous catheter was placed in the cephalic vein for fluid support and 0.9% NaCl solution was administered at a maintenance rate of 3 mL/kg/h throughout the procedure. Following induction with propofol and endotracheal intubation, anaesthesia was maintained with sevoflurane in 100% oxygen, with the vaporiser setting adjusted between 1.5% and 2.5% according to clinical depth.
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Measurement Devices and Application
For HR and SpO2 assessment, a veterinary patient monitor (Monitor 1; Cardell 9405, Sharn Veterinary Inc., Tampa, Florida) was used as the reference method.
HR was measured using the integrated electrocardiography (ECG) function, while SpO2 values were obtained using the monitor's transmittance pulse oximetry (TPO) sensor positioned on the tongue. Electrodes were positioned according to the manufacturer's recommendations, with leads attached to the right forelimb, left forelimb and left hindlimb. HR values were recorded directly from the monitor display.
To verify the accuracy of Monitor 1, simultaneous manual auscultatory HR measurements were performed using a stethoscope over a 30‐s window and extrapolated to beats per minute (bpm). Respiratory rate was determined concurrently by counting visual thoracic excursions over a full 60‐s period to confirm stable respiratory status prior to data pooling.
The OSS (Owlet Smart Sock‐2, Owlet Baby Care Inc., Lehi, UT, USA) was used as the wearable monitoring device. To minimize potential optical artefacts between the sensor and the skin, hair at the tibial application site was clipped using a No.40 blade. The device was placed on the tibial region without the use of additional adhesive tape or bandaging. Its sock‐based design provided adequate fixation at the application site (Figure 1). OSS Size 1 was used in all cats because it provided the most appropriate fit for the body size and distal limb circumference of the study population, ensuring stable sensor positioning and consistent skin contact during monitoring.
[图：The tibial region where HR and SpO2 measurements were obtained using the OSS.]
During the 20‐min data collection window, all cats were maintained in stable right lateral recumbency on a padded surgical table. The OSS was uniformly applied to the left pelvic (the non‐dependent leg) to avoid any weight‐bearing artefacts or compromised localised microcirculation associated with the dependent limb.
For the purposes of statistical analysis and graphical representation, the OSS was designated as ‘Device’, whereas the reference veterinary patient monitor (Cardell 9405) was designated as ‘Monitor 1’.
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Data Collection Procedure
HR and SpO2 measurements were recorded simultaneously using both devices at 1‐min intervals over a 20‐min period. Data acquisition was conducted concurrently by three investigators: one recorded OSS measurements, one documented values obtained from Monitor 1, one performed and recorded auscultatory HR measurements using a stethoscope.
All collected data were transferred into an electronic spreadsheet for subsequent statistical analysis. A total of 307 paired measurements were included in the final analysis.
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Statistical Analysis
All statistical analyses were performed using MedCalc (v. 20.013, MedCalc Software Ltd, Ostend, Belgium). Continuous variables were expressed as mean ± standard deviation (SD) with corresponding 95% confidence intervals (CI). The assumption of normal distribution was assessed using visual inspection methods and descriptive statistics.
Agreement between devices was evaluated using Bland–Altman analysis, with calculation of the mean difference (bias) and the 95% limits of agreement (mean ±1.96 SD). The relationship between measurement differences and the magnitude of measurements was examined using regression analysis.
Clinical equivalence was assessed using the two one‐sided tests (TOST) procedure. Equivalence margins were predefined as ±10 bpm for HR, ±3% for SpO2. A p‐value < 0.05 was considered statistically significant for all analyses.
Linear association between devices was analysed using Pearson correlation analysis, and correlation coefficients (r) together with corresponding p‐values were reported.
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Results
A total of 20 cats were included in the study. Among the measurements obtained using the OSS and Monitor 1, 307 paired HR and SpO2 data points were included in the statistical analysis. The remaining data points were excluded due to synchronisation discrepancies during data collection. Only complete and temporally matched measurements were included in the final analysis.
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Heart Rate
A very strong and statistically significant linear correlation was identified between the OSS and Monitor 1 for HR measurements (r = 0.995, p<0.0001; Table 1, Figure 2)
TABLE 1. Mean difference (bias), 95% limits of agreement derived from Bland–Altman analysis, and correlation coefficients for HR and SpO 2 measurements between the OSS and Monitor 1.
| Parameters | Mean difference (bias) | Lower limit (%) | Upper limit (%) | Correlation ( r ) | p (r) |
|---|---|---|---|---|---|
| HR | 0.224 | −3.36 | 3.81 | 0.995 | <0.0001 |
| SpO 2 | −0.538 | −4.78 | 3.7 | 0.634 | <0.0001 |
[图：Correlation analysis of HR measurements between OSS (Device) and Monitor 1.]
In the Bland–Altman analysis comparing Monitor 1 and the OSS, the mean difference was calculated as 0.224 bpm and was statistically significant (p = 0.0326). The 95% limits of agreement ranged from −3.36 to 3.81 bpm (Table 1; Figure 3).
[图：Bland–Altman analysis of HR measurements between the OSS and Monitor 1.]
Regression analysis demonstrated a statistically significant slope (p = 0.0011).
In the TOST analysis (±10 bpm equivalence margin), the mean difference was 0.18 bpm (95% CI: −0.38–0.40), demonstrating clinical equivalence (p < 0.0001; Table 2).
TABLE 2. Results of the TOST equivalence analysis of HR and SpO 2 measurements between the OSS and Monitor 1.
| Comparison | Mean Difference | 95% CI (bias) | TOST p ‐value | Clinical equivalence |
|---|---|---|---|---|
| HR Monitor 1—Device (bpm) | 0.18 | −0.38–0.40 | <0.0001 | Equivalent |
| SpO 2 Monitor 1—Device (%) | −0.5 | −0.74 to −0.29 | <0.0001 | Equivalent |
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Peripheral Oxygen Saturation
A statistically significant linear correlation was identified between the OSS and Monitor 1 for SpO2 measurements (r = 0.634; p < 0.0001; Table 1; Figure 4).
[图：Correlation analysis of SpO2 measurements between the OSS and Monitor 1, including heat map and regression curve.]
In the Bland–Altman analysis, the mean differences were calculated as −0.538 bpm, with 95% limits of agreement ranging from ‐4.78 to 3.7 bpm (Table 1; Figure 5).
[图：Bland–Altman analysis of SpO2 measurements between the OSS and Monitor 1.]
In the TOST analysis (±3% equivalence margin), the mean difference was ‐0.5% (95% CI: −0.74 to −0.29), indicating clinical equivalence (p < 0.0001; Table 2).
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Discussion
HR and SpO2 are fundamental parameters for assessing cardiopulmonary status in veterinary clinical practice. There is increasing interest in the continuous and non‐invasive monitoring of such vital variables (Cugmas et al. 2019; Yanmaz et al. 2023). Particularly during general anaesthesia, surveillance of these parameters is critical for the early identification of anaesthesia‐related complications (Li et al. 2015; Tamura et al. 2015; Pypendop et al. 2019; Dörfelt et al. 2022). Cats are considered to be at higher risk of anaesthesia‐associated mortality compared with dogs (Dörfelt et al. 2022). Accordingly, the evaluation of reliable monitoring systems is of considerable clinical importance.
Wearable technologies have gained increasing attention in veterinary healthcare in recent years. These systems offer potential advantages, particularly for the non‐invasive and continuous monitoring of cardiorespiratory parameters (Mitek et al. 2022). Photoplethysmography (PPG)‐based systems measure HR and SpO2 by optically detecting variations in tissue blood volume (Cugmas et al. 2019; Hasan and Negulescu 2020). The OSS device operates according to this principle (Hasan and Negulescu 2020). However, fur and pigmented skin may influence light absorption and thereby reduce signal quality; consequently, clipping of the measurement site has been recommended (Cugmas et al. 2019). In the present study, clipping of the tibial region prior to device placement and conducting measurements under anaesthesia were intended to minimise potential optical artefacts and motion‐related signal disturbances.
In human medicine, the OSS device has been reported to provide acceptable accuracy in measuring HR and SpO2 in neonates (Dangerfield et al. 2017). In addition, its use in the early detection of a rare case of ventricular tachycardia has been documented (Young and Flores 2020). However, no studies in the veterinary literature have specifically evaluated the use of the OSS in cats; existing publications primarily address the broader applications of wearable technologies (Mitek et al. 2022).
In the present study, a very strong linear correlation was observed between the OSS and Monitor 1 for HR measurements in healthy cats under general anaesthesia (r = 0.995; p < 0.0001). Bland–Altman analysis demonstrated a mean difference of 0.224 bpm, with 95% limits of agreement ranging from −3.36 to 3.81 bpm. The mean difference was statistically significant (p = 0.0326). In the TOST analysis, clinical equivalence was confirmed within the predefined ±10 bpm equivalence margins (p < 0.0001). These findings indicate that, under controlled anaesthetic conditions, the OSS can provide HR measurements that are consistent with those obtained from Monitor 1.
For SpO2 measurements, a statistically significant linear correlation was identified between the two devices (r = 0.634; p < 0.0001). Bland–Altman analysis revealed a mean difference of −0.538 bpm, with 95% limits of agreement ranging from −4.78 to 3.7 bpm. The mean difference was statistically significant. In the TOST analysis, clinical equivalence was demonstrated within the predefined ±3% equivalence margins (p < 0.0001). However, the lower correlation coefficient compared with HR and the wider limits of agreement suggest greater variability in SpO2 measurements.
In cats, cardiovascular disorders such as hypertrophic cardiomyopathy (Kitz et al. 2019; Şahin et al. 2025), congenital heart diseases (Abboud et al. 2025) and arterial thromboembolism (Kitz et al. 2019; Şahin et al. 2025), as well as respiratory conditions including feline asthma and chronic bronchitis (Chalifoux et al. 2021; Abboud et al. 2025), various forms of pneumonia (Boiron et al. 2019; Abboud et al. 2025), acute lung injury and acute respiratory distress syndrome (Balakrishnan et al. 2017), upper respiratory tract diseases (Chalifoux et al. 2021; Abboud et al. 2025) and pleural effusion (Abboud et al. 2025), may result in clinically significant alterations in HR and SpO2. Accordingly, reliable monitoring of these parameters may facilitate early detection of clinical deterioration in cats at risk of cardiorespiratory disease. However, the findings of the present study are limited to healthy cats under general anaesthesia and should not be directly extrapolated to diseased populations.
The present study has several limitations. The sample size was limited, and only clinically healthy cats classified as ASA I were included. Measurements were performed under general anaesthesia in controlled conditions with minimal movement. Therefore, device performance may differ in conscious and active cats. The OSS was evaluated exclusively on a single anatomical site (the tibia). While the tibial region provided adequate fixation, alternative locations routinely used in veterinary monitoring (such as the metatarsus, digits or base of the tail) were not explored. These sites differ in tissue thickness and vascularity, which may influence light absorption and PPG signal quality. A further limitation is that peripheral perfusion was not objectively quantified using a perfusion index (PI). Because medetomidine may induce peripheral vasoconstriction, the potential influence of altered peripheral perfusion on OSS performance could not be specifically assessed.
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Conclusion
The present study demonstrates that, in healthy cats under general anaesthesia, the OSS exhibits high agreement with the reference monitor for HR measurements and provides clinically acceptable SpO2 values within predefined equivalence margins. These findings indicate that the device may represent a useful non‐invasive tool for monitoring cardiorespiratory parameters under controlled anaesthetic conditions. Nevertheless, because the study was limited to healthy cats, a single sensor placement site and controlled anaesthetic conditions, further investigations involving larger sample sizes, diverse clinical populations, alternative anatomical locations and varying perfusion states are required to confirm and extend these findings.
Author Contributions
Mümin Gökhan Şenocak: methodology, formal analysis. Şule Melek: conceptualization, methodology, supervision, writing – review and editing, writing – original draft. Ömer Tarık Orhun: conceptualization, methodology, data curation, validation. Taner Arslan: data curation.
Funding
This study was supported by the Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (TÜBİTAK).
Ethics Statement
The authors confirm that the ethical policies of the journal, as noted on the journal's author guidelines page, have been adhered to and the appropriate ethical review committee approval has been received. The study protocol was approved by the Atatürk University Animal Experiments Local Ethics Committee (Approval No: 2026/02)
Conflicts of Interest
The authors declare no conflicts of interest.
Acknowledgements
Artificial intelligence was used solely for language and grammar editing. All scientific content and analyses were generated by the authors.
Data Availability Statement
The article data are available from the corresponding author upon request.
References
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Associated Data
Data Availability Statement
The article data are available from the corresponding author upon request.