Assessment of Contact Pressure in Wrist Photoplethysmography and a Multi-Step Mitigation Scheme for Cardiac Measurement Accuracy Enhancements

Q: What are the key findings of this study?

Contact pressure variations significantly impacted PPG heart rate error (p<0.001), with wrist median error rising from 2.38 bpm at near-optimal pressure (Type 2E+2L) to 3.24 bpm at excessive pressure.

Q: What is the clinical evidence from this study?

Study design: Observational. Population: Healthy adults undergoing wrist and finger photoplethysmography (PPG) heart rate measurement (n=27). Intervention: Sub-optimal wrist PPG contact pressure (excessive Type 1L or low Type 1 waveform morphology) vs. Near-optimal wrist PPG contact pressure (Type 2E + Type 2L waveform morphology) against Polar H10 ECG ground truth. Primary outcome: Median wrist PPG heart rate error (absolute difference between ECG and PPG heart rate in bpm) across waveform morphology classes (Kruskal-Wallis H(3) = 52.74, epsilon-squared = 0.015, p=<0.001).

Q: What does this research mean for the field?

Variations in wearable contact pressure significantly degrade photoplethysmography (PPG) heart rate accuracy, increasing wrist median heart rate error from 2.38 bpm under near-optimal pressure to 3.24 bpm under excessive pressure. Novelty: ClaimNovelty.CONFIRMATORY. Consensus alignment: ConsensusAlignment.NEUTRAL.

Q: What question did this study set out to answer?

To evaluate how variations in contact pressure and altered photoplethysmography waveform morphology impact the accuracy of heart rate and blood oxygen saturation readings.

Seojin Lee

doi:10.58445/rars.4261

October 14, 2026Open Access

Assessment of Contact Pressure in Wrist Photoplethysmography and a Multi-Step Mitigation Scheme for Cardiac Measurement Accuracy Enhancements

View Full Paper

Ask AI

Bookmark

Share

Key result

Excessive wrist PPG contact pressure is linked to ~0.9 bpm higher heart rate error.

Kruskal-Wallis H(3) = 52.74, epsilon-squared = 0.015
P<0.001
n=27

Why the study?

Photoplethysmography sensors in commercial wearables are vulnerable to variations in wrist contact pressure, which can deform waveform morphology and cause inaccurate estimation of health metrics such as heart rate.

Does contact pressure (represented by PPG waveform morphology types) affect heart rate measurement accuracy of wrist and finger photoplethysmography compared to ground truth ECG in young, healthy adults?

Key Points

To evaluate how variations in contact pressure and altered photoplethysmography waveform morphology impact the accuracy of heart rate and blood oxygen saturation readings.
Conducted a secondary data analysis of the WF-PPG dataset evaluating wrist and finger photoplethysmography (PPG) against chest electrocardiography (ECG) across 27 seated participants (mean age 24.3 ± 2.7 years).
Categorized PPG cycles into waveform morphology classes associated with varying contact pressures, assessing median absolute heart rate error across N=3,471 wrist cycles and N=3,505 finger cycles.
Assessed fingertip pulse oximeter blood oxygen saturation (SpO2, N=39,822 cycles) relative to normalized contact pressure and heart rate error using Pearson and Spearman correlation analyses.
Wrist PPG median heart rate error differed significantly across morphology classes (H(3) = 52.74, p < 0.001; ε² = 0.015), measuring 2.38 bpm for Type 2E + Type 2L, 2.71 bpm for Type 1, 3.24 bpm for Type 1L, and 2.25 bpm for noise-corrupted Type 3.
Finger PPG median heart rate error differed significantly across morphologies (H(4) = 214.85, p < 0.001; ε² = 0.061), rising as shapes departed from the optimal waveform: Type 2L (1.36 bpm), Type 2E (1.70 bpm), Type 3 (2.16 bpm), Type 1L (2.67 bpm), and Type 1 (5.06 bpm).
Fingertip SpO2 showed a statistically significant but negligible correlation with normalized contact pressure (r = 0.0585, p < 0.001; R² = 0.0034) and no statistically significant relationship with heart rate error (r = 0.0087, p = 0.0836).

Study Design

Type

Observational (n=27)

Multicenter

No

Structured PICO

Does contact pressure (represented by PPG waveform morphology types) affect heart rate measurement accuracy of wrist and finger photoplethysmography compared to ground truth ECG in young, healthy adults?

P

Population

27 young, healthy adults (mean age 24.3 years, 40.7% female) from the WF-PPG dataset who underwent six 4-minute seated recording sessions with varying wrist PPG contact pressures.

E

Exposure

Wrist photoplethysmography (PPG) (measured via MAXM86161 optical modules mounted on a mechanical clamp with an FX1901 load cell sensor across six 4-minute sessions of gradually increasing contact pressure) and finger PPG (attached with a strap at a constant reference pressure).

C

Comparator

Ground truth electrocardiography (ECG) measured via a Polar H10 ECG chest band, synchronized cycle-by-cycle with PPG signals.

O

Outcome

Median heart rate error (defined as the median absolute difference between PPG heart rate and ground truth ECG heart rate, |HRECG − HRPPG|, in bpm) across five PPG waveform morphology categories representing varying contact pressure levels.surrogate

Main Result

Effect estimate: Kruskal-Wallis H(3) = 52.74, epsilon-squared = 0.015

Absolute Event Rate: 3.24% vs 2.38%

p-value: p=<0.001

Variations in wearable contact pressure deform PPG waveform morphology and significantly impact heart rate measurement accuracy compared to ECG, highlighting the need for hardware and algorithmic mitigation schemes in consumer wearables.

Limitations

Dataset consisted only of young, healthy adults (mean age 24.3 years), limiting generalizability to older populations or those with hypertension or stiffer vascular walls
Participants were tested only in a stationary seated position rather than during dynamic physical exercise
Relatively few wrist PPG cycles (8.33% overall; only 43 cycles after filtering) exhibited the ideal Type 2L morphology
Approximately 91% of indexed cycles were excluded from the heart rate analysis, and exclusion was uneven across morphology types
Each pulse cycle was treated as an independent observation despite clustering within participants and sessions, which artificially deflates p-values
The WF-PPG dataset consists only of young, healthy adults (mean age 24.3 ± 2.7 years), limiting generalizability to older demographics with stiffer vascular walls or hypertension.
Participants were tested in a seated position throughout the whole experiment rather than during dynamic, unconstrained physical exercise.
The wrist PPG data had relatively few cycles (8.33%) of the ideal Type 2L morphology, leaving only 43 of 3,316 wrist Type 2L cycles for the heart rate analysis after filtering.
About 91% of the indexed cycles were excluded from the heart rate analysis, and this exclusion was uneven across morphology types.
Each cycle was treated as an independent observation despite cycles from the same participant and session being related, making p-values smaller than they should be.

Implication

Excessive contact pressure may increase wrist PPG heart rate error; leaves open prospective validation of optimal pressure standardization.

Abstract

Modern commercial wearables utilize photoplethysmography (PPG) sensors to track health metrics with a lightweight, compact design.However, PPG sensors are vulnerable to variations in contact pressure, which refers to the level of tightness of wearables on the wrist.This can cause deformation of PPG waveform morphology and result in inaccurate estimation of health metrics.Electrocardiography (ECG) sensors are the gold standard for heart rate measurement, but they contain certain flaws.We assessed how contact pressure affects wrist PPG heart rate accuracy.In this study, we conducted a secondary data analysis on the publicly available WF-PPG dataset.From the dataset, we computed heart rate from both PPG and ECG signals and compared them to calculate heart rate error.The values of heart rate error were distributed across categories based on PPG waveform morphology types, each associated with a range of contact pressure.Thus, the impact of skin composition on the effect of contact pressure was partially accounted for.Median heart rate error for each category was calculated.The results suggested that contact pressure has a profound impact on the accuracy of PPG sensors.Median wrist error was lowest for Type 2E + 2L (2.38 bpm), except for Type 3 (2.25 bpm), which has a low signal-to-noise ratio (SNR); finger error was lowest for Type 2L (1.36 bpm).Blood oxygen saturation (SpO 2 ), measured by a fingertip pulse oximeter, was found to be only negligibly correlated with contact pressure.The results highlight potential inaccuracy in consumer-grade medical data that should be considered during medical use.A multi-step engineering scheme was suggested to alleviate this challenge of modern wearables.

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Seojin Lee (2026) conducted an observational in Healthy adults undergoing wrist and finger photoplethysmography (PPG) heart rate measurement (n=27). Sub-optimal wrist PPG contact pressure (excessive Type 1L or low Type 1 waveform morphology) vs. Near-optimal wrist PPG contact pressure (Type 2E + Type 2L waveform morphology) against Polar H10 ECG ground truth was evaluated on Median wrist PPG heart rate error (absolute difference between ECG and PPG heart rate in bpm) across waveform morphology classes (Kruskal-Wallis H(3) = 52.74, epsilon-squared = 0.015, p=<0.001). Contact pressure variations significantly impacted PPG heart rate error (p<0.001), with wrist median error rising from 2.38 bpm at near-optimal pressure (Type 2E+2L) to 3.24 bpm at excessive pressure.

synapsesocial.com/papers/6ae28e56cbadf70daf6c4201 https://doi.org/10.58445/rars.4261

View Full Paper

Ask AI

Bookmark

Share

Assessment of Contact Pressure in Wrist Photoplethysmography and a Multi-Step Mitigation Scheme for Cardiac Measurement Accuracy Enhancements

Key Points

Study Design

Structured PICO

Main Result

Limitations

Implication

Abstract

Discussion

Cite This Study

Assessment of Contact Pressure in Wrist Photoplethysmography and a Multi-Step Mitigation Scheme for Cardiac Measurement Accuracy Enhancements

Key Points

Study Design

Structured PICO

Main Result

Limitations

Implication

Abstract

Discussion

Cite This Study

Keep reading

Keep reading