Bluetooth Low Energy Beacon Sensors to Document Handheld Magnifier Use at Home by People with Low Vision

Ava K Bittner, Max Estabrook, Niki Dennis, Ava K Bittner, Max Estabrook, Niki Dennis

Abstract

We explored the feasibility of using Bluetooth low energy (BLE) beacon sensors to determine when individuals with low vision (LV) use handheld magnifiers at home. Knowing the frequency and duration of magnifier use would be helpful to document increased magnifier use after successful rehabilitation training, or conversely, to know when someone has abandoned a magnifier and requires assistance. Estimote Sticker BLE beacon sensors were attached to the handles of optical handheld magnifiers and dispensed to eight LV subjects to use at home. Temperature and motion data from the BLE beacon sensors were collected every second by a custom mobile application on a nearby smartphone and transmitted to a secure database server. Subjects noted the date and start/end times of their magnifier use in a diary log. Each of the 99 diary-logged self-reports of magnifier use across subjects was associated with BLE beacon sensor recordings of motion (mean 407 instances; SD 365) and increased temperature (mean 0.20 °C per minute; SD 0.16 °C) (mean total magnitude 5.4 °C; SD 2.6 °C). Diary-logged duration of magnifier use (mean 42 min; SD 24) was significantly correlated with instances of motion (p < 0.001) and rate of temperature increase (p < 0.001) recorded by the BLE beacon sensors. The BLE beacon sensors reliably detected meaningfully increased temperature, coupled with numerous instances of motion, when magnifiers were used for typical reading tasks at home by people with LV.

Keywords: Bluetooth low energy beacon sensors; low vision; magnifier; vision rehabilitation; visual impairment.

Conflict of interest statement

The authors declare no conflict of interest relevant to the topic of this presentation. The sponsors had no role in the design, execution, interpretation, or writing of the study.

Figures

Figure 1
Figure 1
One graph from each participant to display the beacon sensor data for longitudinally collected temperature (black line) and motion, represented by the grey vertical lines, for one diary-logged period for magnifier use, along with additional time shown immediately preceding and subsequent to the magnifier usage. (a) Subject 1 reported using the magnifier for 10 min, when the beacon sensor recorded 109 instances of motion and a total temperature increase of 2.25 °C. (b) Subject 2 reported using the magnifier for 30 min, when the beacon sensor recorded 209 instances of motion and a total temperature increase of 3.7 °C. (c) Subject 3 reported using the magnifier for 30 min, when the beacon sensor recorded 196 instances of motion and a total temperature increase of 4.6 °C. (d) Subject 4 reported using the magnifier for 20 min, when the beacon sensor recorded 230 instances of motion and a total temperature increase of 8.3 °C. (e) Subject 5 reported using the magnifier for 20 min, when the beacon sensor recorded 372 instances of motion and a total temperature increase of 3.5 °C. (f) Subject 6 reported using the magnifier for 24 min, when the beacon sensor recorded 193 instances of motion and a total temperature increase of 4.8 °C. (g) Subject 7 reported using the magnifier for 90 min, when the beacon sensor recorded 468 instances of motion and a total temperature increase of 8.8 °C. (h) Subject 8 reported using the magnifier for 40 min, when the beacon sensor recorded 447 instances of motion and a total temperature increase of 3.4 °C.
Figure 2
Figure 2
Box plots to show the distribution of the beacon sensor data across all subjects for: (A) the number of instances of motion per magnifier use, (B) rate of temperature change and (C) total temperature rise during each magnifier use. In the box plots, the bottom and top of the box are the 25th and 75th percentile (i.e., the upper and lower quartiles, respectively), and the band near the middle of the box is the 50th percentile (i.e., the median). The ends of the whiskers represent the lowest datum within 1.5 times the interquartile range of the lower quartile and the highest datum still within 1.5 times the interquartile range of the upper quartile. Outlier data are represented by individual dots.
Figure 3
Figure 3
Scatter plots to display the data for the self-reported duration of magnifier use from the diary logs in relation to data recorded by the beacon sensor during the period of magnifier use for: (A) the number of instances of detected motion, and (B) the mean rate of temperature rise. (A) The linear fitted line excludes three outlier data points with greater than 1300 instances of motion. (B) The fitted line is a curve for the predicted fractional polynomial.

References

    1. Dougherty B.E., Kehler K.B., Jamara R., Patterson N., Valenti D., Vera-Diaz F.A. Abandonment of low-vision devices in an outpatient population. Optom. Vis. Sci. 2011;88:1283–1287. doi: 10.1097/OPX.0b013e31822a61e7.
    1. Gobeille M.R., Malkin A.G., Jamara R., Ross N.C. Utilization and Abandonment of Low Vision Devices Prescribed on a Mobile Clinic. Optom. Vis. Sci. 2018;95:859–864. doi: 10.1097/OPX.0000000000001267.
    1. Chan T.L., Goldstein J.E., Massof R.W. Low Vision Research Network Study Group. Comparison of clinician-predicted to measured low vision outcomes. Optom. Vis. Sci. 2013;90:776–787.
    1. Huang J., Lentsch M.J., Marsack J.D., Anderson H.A. Evaluating the use of a temperature sensor to monitor spectacle compliance in warm versus cold climates. Clin. Exp. Optom. 2019;102:147–153. doi: 10.1111/cxo.12843.
    1. Aguilar-Rivera M., Erudaitius D.T., Wu V.M., Tantiongloc J.C., Kang D.Y., Coleman T.P., Baxter S.L., Weinreb R.N. Smart Electronic Eyedrop Bottle for Unobtrusive Monitoring of Glaucoma Medication Adherence. Sensors. 2020;20:2570. doi: 10.3390/s20092570.
    1. Petersen C.L., Minor C.M., Mohieldin S., Park L.G., Halter R.J., Batsis J.A. Remote Rehabilitation: A Field-Based Feasibility Study of an mHealth Resistance Exercise Band; Proceedings of the 2020 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies; Crystal City, VA, USA. 16–18 December 2020; pp. 5–6.
    1. Chen C.H., Wang C.C., Chen Y.Z. Intelligent Brushing Monitoring Using a Smart Toothbrush with Recurrent Probabilistic Neural Network. Sensors. 2021;21:1238. doi: 10.3390/s21041238.
    1. Wray T., Chan P.A., Simpanen E., Operario D. eTEST: Developing a Smart Home HIV Testing Kit that Enables Active, Real-Time Follow-Up and Referral after Testing. JMIR Mhealth Uhealth. 2017;5:e62. doi: 10.2196/mhealth.6491.
    1. Aldeer M., Javanmard M., Martin R.P. A Review of Medication Adherence Monitoring Technologies. Appl. Syst. Innov. 2018;1:14. doi: 10.3390/asi1020014.
    1. Chan A.M., Selvaraj N., Ferdosi N., Narasimhan R. Wireless patch sensor for remote monitoring of heart rate, respiration, activity, and falls; Proceedings of the 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC); Osaka, Japan. 3–7 July 2013; pp. 6115–6118.
    1. Komai K., Fujimoto M., Arakawa Y., Suwa H., Kashimoto Y., Yasumoto K. Elderly person monitoring in day care center using Bluetooth Low Energy; Proceedings of the 2016 10th International Symposium on Medical Information and Communication Technology (ISMICT); Worcester, MA, USA. 20–23 March 2016; pp. 1–5.
    1. Ramezani R., Zhang W., Xie Z., Shen J., Elashoff D., Roberts P., Stanton A., Eslami M., Wenger N., Sarrafzadeh M., et al. A Combination of Indoor Localization and Wearable Sensor-Based Physical Activity Recognition to Assess Older Patients Undergoing Subacute Rehabilitation: Baseline Study Results. JMIR Mhealth Uhealth. 2019;7:e14090. doi: 10.2196/14090.
    1. AL-Madani B., Orujov F., Maskeliūnas R., Damaševičius R., Venčkauskas A. Fuzzy Logic Type-2 Based Wireless Indoor Localization System for Navigation of Visually Impaired People in Buildings. Sensors. 2019;19:2114. doi: 10.3390/s19092114.
    1. Bittner A.K., Jacobson A.J., Khan R. Feasibility of Using Bluetooth Low Energy Beacon Sensors to Detect Magnifier Usage by Low Vision Patients. Optom. Vis. Sci. 2018;95:844–851. doi: 10.1097/OPX.0000000000001266.
    1. Macnamara A., Chen C.S., Davies A., Sloan C., Loetscher T. Low vision devices for age-related macular degeneration: A systematic review. Disabil. Rehabil. Assist. Technol. 2021;20:1–13. doi: 10.1080/17483107.2021.1966523.

Source: PubMed

3
Abonnere