Glabella. Continuously Sensing Blood Pressure Behavior using an Unobtrusive Wearable Device. Christian Holz Edward Wang Microsoft Research

Transcription

1 Glabella Continuously Sensing Blood Pressure Behavior using an Unobtrusive Wearable Device Christian Holz Edward Wang Microsoft Research

2 Glabella

3

4 continuously records the pulse at 3 locations, pulse transit time (PTT) continuously predicts blood pressure behavior (inversely correlated with PTT)

5 example: getting up after leaning back optical signals computed pulse transit times sec 10 sec 15 sec 20 sec

6 example: getting up after leaning back optical signals computed pulse transit times sec 10 sec 15 sec 20 sec getting up

7 example: getting up after leaning back optical signals computed pulse transit times sec 10 sec 15 sec 20 sec getting up blood pressure restores

8 introduction

9 blood pressure ~75 million American adults have high blood pressure (32%) high blood pressure was a primary cause of death for more than 410,000 Americans in in 5 American adults is unaware of having high blood pressure

10 blood pressure capture invasive gold standard (clinical settings) semi-automated cuff-based monitor

11 blood pressure during the day

12 blood pressure during the day additionally influenced by short-term events eating and drinking Smith et al., Physiology & Behavior 1997 events at work Lindquist et al., Hypertension 1997 exercise or postural changes Imholz et al., Cardiovascular Research 1990 medication intake

13 continuous monitoring is desirable

14 readily available and accurate suitable for long-term tracking needs correct attachment takes time less suitable in a mobile setting oscillometric cuff device

15 pulse transit time := the time it takes a pulse wave to travel between two sites of the body t 0 requires no cuff and can be measured during each beat t 1 repeatedly shown to correlate highly with blood pressure the hope

16 pulse transit time vs. blood pressure PTT vs. SBP 280 r = TD ( ms ) E - T PTT Nitzan et al. Physiol Meas 2002 Shahrbabaki et al. EMBC 2016 Mukkamala et al. Trans Biomed Eng 2015

17 McCombie et al. EMBC 2006 Liu et al. Sensors 2015 Beckmann et al. EMBC 2017

18 integrated form factor requires no user interaction

19 superficial temporal artery occipital artery

20 superficial temporal artery occipital artery angular artery

21 Glabella cuff-less, wearable, continuous blood pressure monitoring

22 dominant goal: a socially acceptable form factor a lightweight and unobtrusive form factor that directly integrates into the frame of glasses without causing distraction to either the wearer or surrounding people lasts a full day on a single charge while collecting continuous measurements goal

23 V1 V2

24 V2 V3

25 V3 V4

26 fully integrated & standalone Glabella V5 prototype

27 Glabella prototype main board and battery optical sensors

28 Glabella prototype continuously collects 3 optical reflections (at up to 5 khz) 3-DOF inertial motions (at 200 Hz) 15 hours runtime 45 grams in weight

29 electronics

30 Glabella s main board power switch FPC connectors SD IMU PSoC USB

31 Glabella s main board 305 mah LiPo battery real-time clock

32 Glabella s optical pulse sensor board skin-facing back photodiode LED opamp & filter circuit

33 Glabella s optical pulse sensor board flex PCB cables connect to the main board

34 mechanical design

35 off-the-shelf metal-frame glasses parametrized frame 3D printed with digital ABS mechanical design

36 to fit a wearer s head dimensions to ensure sensor contact mechanical design parameters

37 testing amplification circuit in-lab pilot tests quick dimensioning adjustable prototype frame

38 underfilled sensor underfilled hot glue to sustain constant skin contact

39 3D printed nose pad with embedded, underfilled optical sensor

40 signal processing

41 3 optical signals angular artery (nose pad) superficial temporal artery occipital artery (behind ear) s ang s sta s occ

42 1filter optical signals 2analyze the dominant frequency of each optical signal detect pulses and extract temporal features validate candidate features compute pulse transit times signal processing

43 raw signal recordings filtered signals voltage (0..3.3V) sec 2 sec 3 sec 4 sec 5 sec filter optical signals 1 sec 2 sec 3 sec 4 sec 5 sec bandpass filter (0.4 Hz, 8 Hz)

44 apply Fast Fourier transform to each 15-second window to extract dominant frequencies f ang, f sta, f occ derive heart rate if f ang f sta < ε and f ang f occ < ε otherwise discard this window for feature extraction 2derive the dominant frequencies

45 sec 0.4 sec 0.6 sec 0.8 sec detect pulses, extract temporal features

46 local peak nd derivative peak t ang sec 0.4 sec 0.6 sec 0.8 sec detect pulses, extract temporal features

47 discard if IMU variance exceeds a threshold correlate normalized optical signals to assess signal quality phase offset 50 highest-correlating phase shifts 4validate candidate features

48 pulse transit time between the sensors on superficial temporal artery & angular artery occipital artery & angular artery PTT ang sta := t ang t sta PTT ang occ := t ang t occ 5compute pulse transit times

49 example: getting up after leaning back bandpass filtered signals computed pulse transit times sec 10 sec 15 sec 20 sec getting up blood pressure restores

50 in-the-wild evaluation

51 sustain operation and capture useful data during everyday wear and regular activities determine the correlation between the pulse transit times recorded by our prototype and systolic blood pressure values measured by a cuff-based monitor goals

52 wear the custom-fit prototype glasses at least 12 hours per day record blood pressure values three times an hour at least 30 measurements per day 5 days of participation task

53 Glabella device oscillometric device task

54 screening session for custom fitting and instructions procedure

55 charger & cables blood pressure cuff custom-fit Glabella device procedure

56 pick up the box wear the custom-fit prototype and record measurements from Monday through Friday procedure

57 4 participants 2 female (ages 25 and 39) 2 male (ages 40 and 42) all had Fitzpatrick Skin Type II no known related medical conditions (e.g., hypertension) Microsoft employees in different capacities $400 gratuity depending on compliance participants

58 analyzed surrounding ±2 minutes of each blood pressure measurement to predict the wearer s heart rate systolic blood pressure results

59 heart-rate correlations

60 heart-rate correlations

61 heart-rate correlations

62 heart-rate correlations

63 heart-rate correlations

64 histogram: systolic blood pressure

65 PTT ang sta vs. systolic blood pressure

66 PTT ang sta vs. systolic blood pressure

67 PTT ang sta vs. systolic blood pressure

68 PTT ang occ vs. systolic blood pressure

69 PTT ang occ vs. systolic blood pressure

70 conclusion

71 feasibility to continuously collect optical pulse reflections to track heart rates and extract meaningful differences in time-of-arrival established that Glabella tracks blood pressure behavior cuff-less, passively, and conveniently without demanding user input throughout the day and regular activities

72 numerous benefits sensing on the angular artery constant force due to gravity no adjustment necessary best PTT results sensing on angular artery and superficial temporal artery

73 for absolute blood pressure values, simple linear per-user model can predict systolic blood pressure values within ±10 mmhg (assuming correct cuff use)

74 number of participants controlled in-lab study with a continuous baseline calibration is a significant challenge limitations & future work

75 Glabella Continuously Sensing Blood Pressure Behavior using an Unobtrusive Wearable Device Christian Holz

76 Alexander Ching, Christopher O Dowd Mike Sinclair, Jason Goldstein, Sokunthea Neang Daniel Cletheroe, Pavel Kulik, Andrew Carek Kambria Tabor Acknowledgments

77 Glabella Continuously Sensing Blood Pressure Behavior using an Unobtrusive Wearable Device Christian Holz