Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Apr 9;9(4):e27336.
doi: 10.2196/27336.

Force-Sensitive Mat for Vertical Jump Measurement to Assess Lower Limb Strength: Validity and Reliability Study

Erik Vanegas #  1 , Yolocuauhtli Salazar #  2 , Raúl Igual #  1 , Inmaculada Plaza #  1
Affiliations

Force-Sensitive Mat for Vertical Jump Measurement to Assess Lower Limb Strength: Validity and Reliability Study

Erik Vanegas et al. JMIR Mhealth Uhealth. .

Abstract

Background: Vertical jump height is widely used in health care and sports fields to assess muscle strength and power from lower limb muscle groups. Different approaches have been proposed for vertical jump height measurement. Some commonly used approaches need no sensor at all; however, these methods tend to overestimate the height reached by the subjects. There are also novel systems using different kind of sensors like force-sensitive resistors, capacitive sensors, and inertial measurement units, among others, to achieve more accurate measurements.

Objective: The objective of this study is twofold. The first objective is to validate the functioning of a developed low-cost system able to measure vertical jump height. The second objective is to assess the effects on obtained measurements when the sampling frequency of the system is modified.

Methods: The system developed in this study consists of a matrix of force-sensitive resistor sensors embedded in a mat with electronics that allow a full scan of the mat. This mat detects pressure exerted on it. The system calculates the jump height by using the flight-time formula, and the result is sent through Bluetooth to any mobile device or PC. Two different experiments were performed. In the first experiment, a total of 38 volunteers participated with the objective of validating the performance of the system against a high-speed camera used as reference (120 fps). In the second experiment, a total of 15 volunteers participated. Raw data were obtained in order to assess the effects of different sampling frequencies on the performance of the system with the same reference device. Different sampling frequencies were obtained by performing offline downsampling of the raw data. In both experiments, countermovement jump and countermovement jump with arm swing techniques were performed.

Results: In the first experiment an overall mean relative error (MRE) of 1.98% and a mean absolute error of 0.38 cm were obtained. Bland-Altman and correlation analyses were performed, obtaining a coefficient of determination equal to R2=.996. In the second experiment, sampling frequencies of 200 Hz, 100 Hz, and 66.6 Hz show similar performance with MRE below 3%. Slower sampling frequencies show an exponential increase in MRE. On both experiments, when dividing jump trials in different heights reached, a decrease in MRE with higher height trials suggests that the precision of the proposed system increases as height reached increases.

Conclusions: In the first experiment, we concluded that results between the proposed system and the reference are systematically the same. In the second experiment, the relevance of a sufficiently high sampling frequency is emphasized, especially for jump trials whose height is below 10 cm. For trials with heights above 30 cm, MRE decreases in general for all sampling frequencies, suggesting that at higher heights reached, the impact of high sampling frequencies is lesser.

Keywords: force-sensitive resistor; leg strength; lower limb strength; mHealth; mobile health; vertical jump.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Different layers comprising a force-sensitive resistor matrix with smaller dimensions.
Figure 2
Figure 2
Example of a smaller size matrix and how layers are placed.
Figure 3
Figure 3
Developed force-sensitive resistor sensor mat.
Figure 4
Figure 4
Block diagram of the proposed system.
Figure 5
Figure 5
Countermovement jump technique, step by step.
Figure 6
Figure 6
Countermovement jump with arm swing technique, step by step.
Figure 7
Figure 7
Experimental setup used for proposed experiments.
Figure 8
Figure 8
Two volunteers performing the proposed protocol showing the different phases of the jumps: takeoff frame, maximum-height frame, and landing frame.
Figure 9
Figure 9
Correlation graph comparing both measuring methods for the first experiment, showing a coefficient of determination of R2=.996.
Figure 10
Figure 10
Bland-Altman plot of both measuring methods: countermovement jump depicted by dark gray points and countermovement jump with arm swing depicted by light gray points.
Figure 11
Figure 11
Normalized mean absolute error and mean relative error, divided in different ranges of height reached during vertical jump.
Figure 12
Figure 12
Distribution of different height ranges reached by the users. Overall trials, only countermovement jump trials, and only countermovement jump with arm swing trials are shown.
Figure 13
Figure 13
Mean relative error obtained for each proposed sampling frequency. As sampling frequency decreases, relative error increases exponentially.
See this image and copyright information in PMC

References

    1. Rodrigues C, Correia M, Abrantes J, Nadal J, Benedetti Rodrigues MA. Consistency of surface electromyography assessment at lower limb selected muscles during vertical countermovement. Annu Int Conf IEEE Eng Med Biol Soc. 2017 Jul;2017:402–405. doi: 10.1109/EMBC.2017.8036847. - DOI - PubMed
    1. Garcia M, Guzmán L, Valencia J, Henao V. Portable measurement system of vertical jump using an inertial measurement unit and pressure sensors. 2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA); 2016; Bucaramanga. 2016. pp. 1–5. - DOI
    1. Drazan J, Danielsen H, Vercelletto M, Loya A, Davis J, Eglash R. A case study for integrated STEM outreach in an urban setting using a do-it-yourself vertical jump measurement platform. Annu Int Conf IEEE Eng Med Biol Soc. 2016 Aug;2016:3027–3030. doi: 10.1109/EMBC.2016.7591367. - DOI - PubMed
    1. Casartelli N, Müller R, Maffiuletti N. Validity and reliability of the Myotest accelerometric system for the assessment of vertical jump height. J Strength Cond Res. 2010 Nov;24(11):3186–3193. doi: 10.1519/JSC.0b013e3181d8595c. - DOI - PubMed
    1. Mijailovic N, Radakovic R, Peulic A, Milankovic I, Filipovic N. Using force plate, computer simulation and image alignment in jumping analysis. 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE); 2015; Belgrade. 2015. pp. 1–4. - DOI

Publication types

LinkOut - more resources