Reliability of biometric devices for measuring hand grip and finger pinch strength in stroke patients over 50: a prospective observational study

Abstract

The aim of the study was to assess the test–retest reliability, inter-rater reliability of the Biometrics device with regard to hand grip and finger pinch strength in people in the late period after stroke aged over 50 years. A total of 100 individuals in the late period after stroke participated in the study. Two investigators performed hand grip and pinch strength measurements using the Biometrics E-link assessment system. The subjects were examined twice within two weeks, under the same conditions. After conducting the examinations, high consistency of measurements was found both between the investigators and between the examinations using a hand grip dynamometer and a Pinchmeter. For all measurements, high values of Pearson correlation coefficient close to 1, interclass correlation coefficient (ICC) > 0.9 and Cronbach’s alpha index > 0.9 were shown. The width of the LoA interval in the pinchometer measurements (comparison of Study I vs. II for the same examiner) often oscillated around the value of 1.0 or less. In the dynamometer, the results showed repeatability for the right hand (for examiner I: LoA was 3.984; examiner II: LoA–3.470. The study showed that hand grip and pinch strength assessment performed using the Biometrics E-link assessment system show high test–retest reliability and inter-rater reliability. The Biometrics E-link can be recommended for daily clinical practice among people in the late period after stroke.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-025-12712-1.

Introduction

The rapid development of technology and health care still does not ensure a complete recovery for stroke patients. More than half of people after a stroke experience permanent hemiparesis, which makes it difficult to function independently. The return of upper limb function, especially of the hand, remains a major problem. Deficits in hand function affect the activities of everyday life, hence the need for emphasis on motor improvement of the hand¹.

The function of the hand is based on strength, which will be manifested, for example, in a strong grip with simultaneous control of the work of individual fingers and their movement. Limitations in the flexion and extension of the fingers will lead to difficulties with opening the hands and generating a strong grip. These are the most common impairments of hand function in patients after stroke. Lack of control over the fingers results in the inability to perform movements with a single finger and the inability to perform complex gestures. These impairments will manifest themselves in the inability to e.g. close buttons, type on a keyboard².

Effective rehabilitation of a paretic hand depends on proper assessment of motor deficits and selected therapy. In diagnostics, tests, centimetre tapes and goniometers are used.

To measure muscular endurance and strength, isokinetic and static dynamometers are used, which allow for objective measurements. An important element of diagnostics is accuracy, which constantly spurs the development of new tools equipped with sensors, motion tracking systems and robotic devices³.

The use of robotic therapy devices allows for passive and active hand movement and feedback to the patient about the way a task is performed. Another beneficial element is the ability to perform intensive training and motivation of the patient to exercise. There are a number of devices for upper limb therapy, but there is still a lack of devices for improving the hand itself⁴.

One of the devices for hand function rehabilitation is the Biometrics E-link. The high sensitivity and accuracy of measurements using the electronic dynamometer and pinchmeter of this device allows for accurate motor assessment of a paretic hand^5–7. The Biometrics E-link device has been evaluated for reliability in other populations (e.g. healthy individuals^5,8 children with cerebral palsy⁹, patients with rheumatoid arthritis¹⁰, after hand prosthesis¹¹. However, there is a lack of studies on the specific use and validation of the Biometrics E-link device in the population of stroke patients over the age of 50. Hence the interest in research using this device.

The aim of the study was to assess the test–retest reliability, inter-rater reliability of the Biometrics device with regard to hand grip and finger pinch strength in people in the late period after stroke aged over 50 years.

Materials and methods

Participants and setting

Prior to testing, the minimum sample size was calculated using a sample size selection calculator. A minimum sample size of 82 subjects in the late period after stroke was obtained, from which 100 subjects were qualified for the study. It was carried out in accordance with the ethical rules of the Helsinki Declaration, and approved by the Local Bioethics Commission of the University of Rzeszow (consent no. No. 2022/085). Written informed consent was obtained from all participants in the study. The study was registered in the clinical trials register at the site ClinicalTrials.gov (registration number NCT05486052).

The study was conducted at the Spa and Rehabilitation Hospital, Physiotherapy Laboratory, in Poland. The inclusion criteria were defined as follows: completed first ischemic stroke; patient’s informed, voluntary consent to participate; elementary (basic) gripping ability; upper limb and hand paresis rated 4–5 on the Brunnström scale; degree of disability Rankin score of 3; spastic tension of the upper limb and hand paresis not more than 3 on the modified Ashworth scale; and doctor’s agreement to participate in the study. The following exclusion criteria were applied: lack of the patient’s informed, voluntary consent; second or subsequent ischemic stroke of the brain; haemorrhagic stroke; stroke of the brainstem and cerebellum; cerebellum disorders of the higher mental functions limiting the ability to understand and perform tasks during examinations; visual disturbances; mechanical and thermal injuries potentially impairing hand grip function; concomitant disorders.

The mean age in the group was observed at the level of nearly 65 years ( = 64,6). The youngest person was 51 years old (Min. 51.0), and the oldest 75 years old (Max. 75.0). In terms of body weight, body height, BMI and time since stroke, the values averaged over 76 kg ( = 76.3), 169 cm ( = 169.2), 26.5 kg/m² ( = 26.6) and time since stroke 52 months ( = 52.3) (Table 1).

Table 1.

Descriptive statistics—age, body weight, body height, BMI, time since stroke.

Variables	Descriptive statistics
	N		Me	Min	Max	Q1	Q3	SD
Age [years]	100	64,6	65,0	51,0	75,0	60,0	70,0	6,80
Body weight [kg]	100	76.3	78.1	46.9	111.0	69.6	81.6	11.81
Body height [cm]	100	16.,2	169.0	152.0	190.0	164.0	173.5	6.77
BMI [kg/m2]	100	26.6	26.7	17.4	36.2	24.5	28.3	3.55
Time since stroke [months]	100	52.3	25.5	6.0	204.0	8.0	96.0	53.22

N, number of observations; , mean; Me, median; Min., minimum value; Max., maximum value; Q1, lower quartile; Q3, upper quartile, SD, standard deviation, BMI, body mass index.

Procedure

Using the Biometrics E-link electronic dynamometer, which records forces from less than 0.1 kg/lb to 90 kg (200 lb), hand grip strength was assessed. The pinch strength of the fingers was assessed with the Biometrics E-link.

Pinchmeter, which records a force up od 0,1 to 22 kg (50 lb), both measure every 0.1. Accuracy  ± 2% of full scale. These are devices with measurement accuracy, ease and speed of measurement, and demonstrate high sensitivity to recording very small measurements. After connecting the E-LINK DG1 or X4 InterX dongle to the computer, the devices connect to the firmware. The device has diagnostic functions, and through direct connection to the computer, the patient can have hand therapy. The wireless version uses the DG1 dongle and the AD1 adapter^5,12. Prior to data collection, both investigators underwent standardized training to ensure consistent application of the measurement protocol and minimize inter-rater variability. The Biometrics E-link devices were regularly calibrated according to manufacturer specifications. Although the Biometrics E-link device is available and clinically used calibration procedures are used regularly by the manufacturer every 2 years, the manufacturer guarantees the reliability of the measurements performed; however, it appears that more frequent calibration could affect the accuracy and repeatability of measurements, especially in multi-center studies or studies involving different investigators.

The measurements were performed in accordance with the American Society of Hand Therapists (ASHT) guidelines and the Biometrics E-link device reliability assessment methodology for assessing hand grip and finger pinch strength in healthy individuals: arms adducted and neutrally rotated, elbow bent to 90°, forearm in a neutral position and wrist in the range of 0–30° of extension and 0–15° of ulnar deviation and feet flat on the floor^8,13. The methodology for the repeatability of examinations was consistent with the guidelines given in assessment of healthy people. The examination of hand grip and finger pinch strength (key, three jaw chuck, tip-to-tip) was carried out three times for each hand, and all measurements were made by two independent investigators at the same time and under the same conditions. In order to avoid muscle fatigue between trials, 15-s breaks were given. The duration of each contraction was 3 s, and the length of the break after the first examination was 5 min. The length of the break was determined according to the manufacturer’s recommendations and available scientific reports^5,8,12.

Data analysis

The mean value and standard deviation for each series of measurements were calculated, along with the mean and standard deviation of the differences between the compared series of measurements. The assessment of the significance of differences in the mean level of two series of measurements was made using the t-test for dependent samples, in which no significant values should be observed, but it should be remembered that this is not a key factor in assessing the consistency of measurements. The series were compared using Pearson’s linear correlation coefficient, as well as the ICC interclass correlation coefficient, a key measure of the consistency of the two measurements. The Bland–Altman method and the Cronbach alpha coefficient were proposed as alternative measures of consistency. In order to assess intra-rater reliability, the intraclass correlation coefficient (ICC)(2,1) model (Two-Way Random Effects, Absolute Agreement, single measure) was used for each examiner. The choice of this model is justified by the need to assess absolute agreement between two measurements made by the same examiner at different time points. This model takes into account both the variance from the subjects studied and the variance resulting from measurement errors and potential systematic differences between the measurements.

In addition to the ICC, the analysis also assessed the Standard Error of Measurement (SEM), which is a measure of absolute reliability. SEM provides information about the precision of the measurement in the original units (kg), which is crucial for clinical interpretation.

Cronbach’s alpha coefficient was used to assess the overall consistency of the compared pairs of measurements (both in intra-rater and inter-rater analyses). Although this coefficient is usually used to assess the internal consistency of multi-item scales, in this study it was used as a supplementary measure.

The level of statistical significance was p < 0.05.

Results

In terms of the repeatability of measurements for the dynamometer strength assessment, consistency of the recorded values between the examinations, and between the investigators, was observed. For the assessment of the left hand and the right hand between examination I and II, significant differences were noted with the second investigator in mean values, reaching a maximum of 0.71 kg (for the left hand), as well as 0.53 kg between the investigators in examination I for the left hand. Despite the above observation and the differences in means, the key consistency index ICC remained at a high level (0.985–0.997). The consistency of the measurements is also confirmed by high values of Pearson’s linear correlation coefficient (0.96–1.00).

This thesis is also confirmed by the Bland–Altman plots presented below (Table 2, Additional file 1, Additional file 2).

Table 2.

Consistency of measurements between investigators and between examinations for measuring hand strength using a dynamometer.

Study	Investigator	Measurements				Differences				p	r	ICC	CV	SEM	Cronbach’s alpha
			SD	Me	s2		SD	Me	s2
Dynamometer HR–Right hand
I	1	22.48	13.04	19.25	170.16	0.14	2.13	0.10	4.52	0.5208	0..987	0.987 (0.980–0.991)	58.04	1.30	0.993
I	2	22.34	12.79	19.75	163.63								57.26	1.28
II	1	22.58	13.21	20.10	174.61	0.002	2.37	0.05	5.64	0.9933	0.984	0.983 (0.976–0.989)	58.53	1.32	0.992
II	2	22.57	12.80	20.00	163.71								56.68	1.28
I	1	22.48	13.04	19.25	170.16	− 0.10	1.02	0.10	1.03	0.3275	0.997	0.997 (0.996–0.998)	58.04	1.30	0.999
II	1	22.58	13.21	20.10	174.61								58.53	1.32
I	2	22.34	12.79	19.75	163.63	− 0.23	0.89	− 0.10	0.78	0.0092	0.998	0.997 (0.996–0.998)	57.26	1.28	0.999
II	2	22.57	12.80	20.00	163.71								56.68	1.28
Dynamometer HL–Left hand
I	1	21.15	12.92	18.35	166.90	0.53	2.17	0.55	4.70	0.0161	0.965	0.985 (0.977–0.990)	61.09	1.29	0.993
I	2	20.62	12.45	17.10	154.88								60.37	1.24
II	1	21.32	12.95	18.75	167.75	− 0.01	2.13	− 0.20	4.54	0.9701	0.958	0.987 (0.980–0.991)	60.74	1.30	0.993
II	2	21.33	13.02	17.10	169.58								61.05	1.30
I	1	21.15	12.92	18.35	166.90	− 0.18	1.66	− 0.10	2.77	0.2955	0.999	0.992 (0.988–0.994)	61.09	1.29	0.996
II	1	21.32	12.95	18.75	167.75								60.74	1.30
I	2	20.62	12.45	17.10	154.88	− 0.71	1.35	− 0.40	1.81	< 0.001	0.998	0.993 (0.989–0.995)	60.37	1.24	0.997
II	2	21.33	13.02	17.10	169.58								61.05	1.30

, mean; SD, standard deviation; Me, median; s², variance; p, significance assessment of differences of the mean levels of two series of measurements (t test for dependent samples); r, Pearson’s linear correlation coefficient; ICC, interclass correlation coefficient with 95% confidence interval; CV, coefficient of variation; SEM, standard error of mean.

Significant values are in bold.

Next, the consistency of the obtained results for measurements of the strength of the fingers (key) using a pinchmeter was assessed. Significant mean differences of the order of 0.06–0.1 kg were noted for investigator 1 (for the assessment of the right and left hand) and investigator 2 (for the assessment of the right hand) between the values from examination I and II (p < 0.001; p = 0.002). The high values of key consistency assessment tools confirmed similar results during the examinations carried out (ICC 0.957-0.999) (Table 3).

Table 3.

Consistency of measurements between investigators and between examinations for measuring finger strength using a pinchmeter.

Study	Investigator	Measurements				Differences				p	r	ICC	CV	SEM	Cronbach’s alpha
			SD	Me	s2		SD	Me	s2
Pinchmeter HR–Right hand (key)
I	1	6.12	3.74	5.75	13.95	0.11	0.92	0.40	0.85	0.2435	0.969	0.969 (0.954–0.979)	61.04	0.37	0.984
I	2	6.01	3.68	5.30	13.52								61.17	0.37
II	1	6.22	3.74	5.85	14.02	0.13	0.99	0.35	0.99	0.1943	0.964	0.964 (0.947–0.976)	60.17	0.37	0.982
II	2	6.09	3.69	5.35	13.64								60.61	0.37
I	1	6.12	3.74	5.75	13.95	− 0.10	0.22	− 0.10	0.05	< 0.001	0.998	0.998 (0.997–0.999)	61.04	0.37	0.999
II	1	6.22	3.74	5.85	14.02								60.17	0.37
I	2	6.01	3.68	5.30	13.52	− 0.08	0.19	− 0.10	0.04	0.0001	0.997	0.998 (0.998–0.999)	61.17	0.37	0.999
II	2	6.09	3.69	5.35	13.64								60.61	0.37
Pinchmeter HL–Left hand (key)
I	1	5.95	4.12	5.00	16.98	0.15	1.08	0.60	1.18	0.1724	0.965	0.964 (0.947–0.976)	69.29	0.41	0.982
I	2	5.80	3.98	5.10	15.83								68.63	0.40
II	1	6.01	4.10	5.00	16.84	0.17	1.17	0.70	1.38	0.1457	0.958	0.957 (0.937–0.971)	68.32	0.41	0.978
II	2	5.83	3.95	5.00	15.58								67.64	0.39
I	1	5.95	4.12	5.00	16.98	− 0.06	0.19	− 0.10	0.04	0.0016	0.999	0.999 (0.998–0.999)	69.29	0.41	0.999
II	1	6.01	4.10	5.00	16.84								68.32	0.41
I	2	5.80	3.98	5.10	15.83	− 0.04	0.27	− 0.10	0.07	0.1560	0.998	0.998 (0.997–0.998)	68.63	0.40	0.999
II	2	5.83	3.95	5.00	15.58								67.64	0.39

, mean; SD, standard deviation; Me, median; s², variance; p, significance assessment of differences of the mean levels of two series of measurements (t test for dependent samples); r, Pearson’s linear correlation coefficient; ICC, interclass correlation coefficient with 95% confidence interval; CV, coefficient of variation; SEM, standard error of mean.

Significant values are in bold.

Similar conclusions were drawn in relation to the Bland–Altman plots. High consistency of measurements was found in the recorded values with a few exceptions in which the highest difference in mean was observed in examination II between investigator 1 and 2 (0.17 kg). Both between the examinations and between the investigators, the results were similar (Additional file 3, Additional file 4).

The mean differences between the investigators and between the examinations for the measurements of strength (three jaw chuck) of the left hand (except for the measurements by investigator 2) were statistically insignificant, which indicates that similar mean values were recorded. A similar situation was observed for measurements of the right hand, except for the values recorded between examinations by investigator 1 and 2. The most unfavourable differences in the mean values were 0.13 kg (left hand).

In connection with the recording of small differences in means, the consistency of the measurements was confirmed, with high correlation coefficients (r = 0.958–0.999) and high values of the ICC coefficient (0.957–0.999) (Table 4).

Table 4.

Consistency of measurements between investigators and between examinations for measuring finger strength using a pinchmeter (three jaw chuck).

Study	Investigator	Measurements				Differences				p	r	ICC	CV	SEM	Cronbach’s alpha
			SD	Me	s2		SD	Me	s2
Pinchmeter HR–Right hand (three jaw chuck)
I	1	5.88	3.74	5.00	14.02	0.08	0.88	0.15	0.77	0.3649	0.972	0.972 (0.959–0.981)	63.67	0.37	0.986
I	2	5.80	3.67	5.25	13.50								63.35	0.37
II	1	5.95	3.71	5.00	13.78	0.08	0.90	0.05	0.82	0.4024	0.970	0.970 (0.956–0.980)	62.40	0.37	0.985
II	2	5.87	3.68	5.20	13.56								62.70	0.37
I	1	5.88	3.74	5.00	14.02	− 0.07	0.17	− 0.10	0.03	0.0001	0.999	0.999 (0.998–0.999)	63.67	0.37	0.999
II	1	5.95	3.71	5.00	13.78								62.40	0.37
I	2	5.80	3.67	5.25	13.50	− 0.07	0.19	− 0.10	0.04	0.0002	0.999	0.998 (0.998–0.999)	63.35	0.37	0.999
II	2	5.87	3.68	5.20	13.56								62.70	0.37
Pinchmeter HL–Left hand (three jaw chuck)
I	1	5.61	3.90	4.90	15.22	− 0.08	1.04	− 0.45	1.07	0.4363	0.965	0.965 (0.948–0.976)	69.50	0.39	0.982
I	2	5.69	3.92	4.55	15.35								68.81	0.39
II	1	5.65	3.90	5.00	15.17	− 0.17	1.13	− 0.25	1.27	0.1388	0.958	0.957 (0.937–0.971)	68.92	0.39	0.979
II	2	5.82	3.87	4.70	14.96								66.46	0.39
I	1	5.61	3.90	4.90	15.22	− 0.04	0.21	− 0.10	0.04	0.0672	0.999	0.999 (0.998–0.999)	69.50	0.39	0.999
II	1	5.65	3.90	5.00	15.17								68.92	0.39
I	2	5.69	3.92	4.55	15.35	− 0.13	0.28	− 0.10	0.08	< 0.001	0.998	0.997 (0.995–0.998)	68.81	0.39	0.999
II	2	5.82	3.87	4.70	14.96								66.46	0.39

, mean; SD, standard deviation; Me, median; s², variance; p, significance assessment of differences of the mean levels of two series of measurements (t test for dependent samples); r, Pearson’s linear correlation coefficient; ICC, interclass correlation coefficient with 95% confidence interval; CV, coefficient of variation; SEM, standard error of mean.

Significant values are in bold.

Referring to the alternative Bland–Altman measure, a similar conclusion can be drawn. The highest differences were recorded between investigator 1 and 2 in the second examination. It was noted that the differences in measurements, except in individual cases, were in the range of up to a maximum of 2 kg (Additional file 5, Additional file 6).

Taking into account measurements for the strength of the fingers of the right and left hand using a pinchmeter (tip-to-tip), high consistency was found in the results recorded, both between the examinations and between the investigators.

Despite the observation of significant differences in mean values (maximum 0.4 kg between investigators in examination II), the above statement was confirmed by reference to the key measure of ICC consistency, which was recorded at a level of 0.907–0.998 and correlation coefficients (0.92–1.00). The alternative measure of consistency, Cronbach’s alpha, also showed results indicating high consistency of measurements (0.956–0.999) (Table 5).

Table 5.

Consistency of measurements between investigators and between examinations for measuring finger strength using a pinchmeter (tip-to-tip).

Study	Investigator	Measurements				Differences				p	r	ICC	CV	SEM	Cronbach’s alpha
			SD	Me	s2		SD	Me	s2
Pinchmeter HR–Right hand (tip to tip)
I	1	4.73	2.95	4.10	8.73	− 0.02	1.10	0.15	1.22	0.8850	0.928	0.928 (0.895–0.951)	62.45	0.30	0.962
I	2	4.75	2.84	4.15	8.06								59.83	0.28
II	1	4.82	2.94	4.40	8.62	− 0.01	1.11	− 0.05	1.24	0.9216	0.926	0.927 (0.893–0.950)	60.92	0.29	0.962
II	2	4.83	2.85	4.20	8.15								59.08	0.29
I	1	4.73	2.95	4.10	8.73	− 0.09	0.18	− 0.10	0.03	< 0.0001	0.998	0.998 (0.997–0.998)	62.45	0.30	0.999
II	1	4.82	2.94	4.40	8.62								60.92	0.29
I	2	4.75	2.84	4.15	8.06	− 0.08	0.28	− 0.10	0.08	0.0026	0.995	0.995 (0.992–0.997)	59.83	0.28	0.998
II	2	4.83	2.85	4.20	8.15								59.08	0.29
Pinchmeter HL–Left hand (tip to tip)
I	1	4.41	2.95	3.70	8.70	− 0.28	1.09	− 0.60	1.20	0.0129	0.932	0.928 (0.895–0.951)	66.90	0.29	0.965
I	2	4.69	2.98	3.90	8.86								63.52	0.30
II	1	4.43	2.93	3.60	8.59	− 0.40	1.20	− 0.70	1.44	0.0013	0.915	0.907 (0.865–0.936)	66.14	0.29	0.956
II	2	4.83	2.89	4.20	8.34								59.82	0.29
I	1	4.41	2.95	3.70	8.70	− 0.02	0.18	0.00	0.03	0.2064	0.998	0.998 (0.997–0.999)	66.90	0.29	0.999
II	1	4.43	2.93	3.60	8.59								66.14	0.29
I	2	4.69	2.98	3.90	8.86	− 0.14	0.31	− 0.10	0.09	< 0.0001	0.995	0.993 (0.990–0.996)	63.52	0.30	0.997
II	2	4.83	2.89	4.20	8.34								59.82	0.29

, mean; SD, standard deviation; Me, median; s², variance; p, significance assessment of differences of the mean levels of two series of measurements (t test for dependent samples); r, Pearson’s linear correlation coefficient; ICC, interclass correlation coefficient with 95% confidence interval; CV, coefficient of variation; SEM, standard error of mean.

Significant values are in bold.

The highest extreme difference between the two recorded values at ± 5 kg was observed between investigator 1–2 in both examinations for the right and left hand. The lowest mean difference was observed for measurements of the right hand between investigator 1 and 2 in examination II (− 0.011 kg) (Additional file 7, Additional file 8).

In addition to the ICC, the SEM was also assessed in the analysis. For the handgrip strength measurements with a dynamometer, the SEM was about 1.30 kg (Table 2). In contrast, all precision grip strength measurements performed with a pinchmeter were characterized by a significantly lower measurement error: for the key grip, the SEM was about 0.37–0.41 kg (Table 3), for the three-point grip about 0.37–0.39 kg (Table 4), and for the fingertip grip about 0.28–0.30 kg (Table 5).

Detailed evaluation of inter-rater and intra-rater reproducibility using Bland–Altman analysis and a quantitative summary of the results, including the mean difference (bias) and 95% limits of agreement (LoA), are presented in Table 6.

Table 6.

Detailed assessment of inter-rater and intra-rater repeatability based on Bland–Altman analysis.

Comparison	Mean difference (Bias)	95% Limits of agreement (LoA)	Interval width LoA
Dynamometer–Right hand
Researcher 1 versus Researcher 2 (Study I)	0.137	− 4.030 do 4.304	8.334
Researcher 1 versus Researcher 2 (Study II)	0.002	− 4.652 do 4.656	9.308
Researcher 1 (Study I vs. II)	− 0.100	− 2.092 do 1.892	3.984
Researcher 2 (Study I vs. II)	− 0.235	− 1.970 do 1.500	3.470
Dynamometer–Left hand
Researcher 1 versus Researcher 2 (Study I)	0.531	− 3.720 do 4.782	8.502
Researcher 1 versus Researcher 2 (Study II)	− 0.008	− 4.183 do 4.167	8.350
Researcher 1 (Study I vs. II)	− 0.175	− 3.436 do 3.086	6.522
Researcher 2 (Study I vs. II)	− 0.714	− 3.351 do 1.923	5.274
Pinchmeter–Key–Right
Researcher 1 versus Researcher 2 (Study I)	0.108	− 1.696 do 1.912	3.608
Researcher 1 versus Researcher 2 (Study II)	0.130	− 1.820 do 2.080	3.900
Researcher 1 (Study I vs. II)	− 0.104	− 0.543 do 0.335	0.878
Researcher 2 (Study I vs. II)	− 0.082	− 0.461 do 0.297	0.758
Pinchmeter–Key–Left
Researcher 1 versus Researcher 2 (Study I)	0.149	− 1.976 do 2.274	4.250
Researcher 1 versus Researcher 2 (Study II)	0.172	− 2.127 do 2.471	4.598
Researcher 1 (Study I vs. II)	− 0.061	− 0.428 do 0.306	0.734
Researcher 2 (Study I vs. II)	− 0.038	− 0.559 do 0.483	1.042
Pinchmeter–Three jaw chuck–Right
Researcher 1 versus Researcher 2 (Study I)	0.080	− 1.642 do 1.802	3.444
Researcher 1 versus Researcher 2 (Study II)	0.076	− 1.695 do 1.847	3.542
Researcher 1 (Study I vs. II)	-0.069	− 0.408 do 0.270	0.678
Researcher 2 (Study I vs. II)	-0.073	− 0.448 do 0.302	0.750
Pinchmeter–Three jaw chuck–Left
Researcher 1 versus Researcher 2 (Study I)	− 0.081	− 2.112 do 1.950	4.062
Researcher 1 versus Researcher 2 (Study II)	− 0.168	− 2.375 do 2.039	4.414
Researcher 1 (Study I vs. II)	− 0.039	− 0.452 do 0.374	0.826
Researcher 2 (Study I vs. II)	− 0.126	− 0.670 do 0.418	1.088
Pinchmeter–Tip-to-tip–Right
Researcher 1 versus Researcher 2 (Study I)	− 0.016	− 2.178 do 2.146	4.324
Researcher 1 versus Researcher 2 (Study II)	− 0.011	− 2.195 do 2.173	4.368
Researcher 1 (Study I vs. II)	− 0.090	− 0.440 do 0.260	0.700
Researcher 2 (Study I vs. II)	− 0.085	− 0.624 do 0.454	1.078
Pinchmeter–Tip-to-tip–Left
Researcher 1 versus Researcher 2 (Study I)	− 0.277	− 2.422 do 1.868	4.290
Researcher 1 versus Researcher 2 (Study II)	− 0.396	− 2.747 do 1.955	4.702
Researcher 1 (Study I vs. II)	− 0.023	− 0.377 do 0.331	0.708
Researcher 2 (Study I vs. II)	− 0.142	− 0.744 do 0.460	1.204

For the right-hand grip strength measurements obtained with the dynamometer, the comparison between Examiner 1 and Examiner 2 in the first study showed a mean difference of 0.137 with a LoA of 8.334. In the second study, the inter-rater agreement for the same hand was characterized by a smaller bias (0.002) but a wider LoA (9.308). The analysis of reproducibility for the right hand was more favorable, with Examiner 1 having a LoA of 3.984 and Examiner 2 having a LoA of 3.470. For the left hand, inter-rater agreement was similar in both studies, with LoA widths of 8.502 in the first study and 8.350 in the second. Repeatability for the left hand was lower than for the right; LoA widths were 6.522 for Examiner 1 and 5.274 for Examiner 2.

Analysis of pinchmeter measurements included three grip types. For the right key grip, inter-rater agreement yielded LoA widths of 3.608 (Study I) and 3.900 (Study II). The repeatability for this grip was very high, with an LoA of only 0.878 for Examiner 1 and 0.758 for Examiner 2. The results for the left key grip were similar: inter-examiner LoAs of 4.250 and 4.598 across studies, and the repeatability for Examiners 1 and 2 was characterized by LoAs of 0.734 and 1.042, respectively. For the right three-point grip, the inter-examiner LoAs of 3.444 (Study I) and 3.542 (Study II) were very high, with LoAs of 0.678 (Examiner 1) and 0.750 (Examiner 2). For the left hand, the values were slightly higher: inter-rater agreement gave LoA widths of 4.062 and 4.414, and inter-rater repeatability of 0.826 and 1.088. The last grip tested, the right bulbar grip, showed inter-rater LoA widths of 4.324 and 4.368, and its repeatability was characterized by a range of 0.700 (Researcher 1) and 1.078 (Researcher 2). For the left bulbar grip, inter-rater agreement gave LoA widths of 4.290 and 4.702, and inter-rater repeatability of 0.708 and 1.204.

Discussion

The aim of the study was to assess the test–retest reliability, inter-rater reliability of the Biometrics device with regard to hand grip and finger pinch strength in people in the late period after stroke aged over 50 years. The study has shown that assessments carried out with the Biometrics E-link assessment system show high test–retest reliability and inter-rater reliability.

Our research has a practical dimension, confirming the usefulness of the Biometrics device in assessing hand grip and finger pinch strength in people in the late period after stroke, which is important due to the fact that stroke is a very large social problem. Studies indicate that in the coming years, the number of stroke sufferers requiring rehabilitation will increase¹⁴, and many stroke survivors will face the consequences of the illness in the form of hand-function disorders, including hand grip and pinch strength¹⁵. This makes it crucial to introduce credible and reliable assessment methods in this area, which will allow for proper planning and monitoring of therapy programs, individually tailored to the patient, and thus increase the patient’s chances of independence in everyday life³. Therefore, our results provide scientific evidence that the Biometrics E-link can be recommended for everyday clinical practice as a tool for assessing hand function in late stroke patients.

There is so far a lack of research in the national literature on the assessment of the test–retest reliability and inter-rater reliability of Biometrics devices in patients in the late period after stroke, so the results we have obtained provide new knowledge in this area. The identified research gap is important for several reasons. First, in the late post-stroke period, a much slower rate of functional changes is observed compared to the acute and subacute phases. This means that the tools used to monitor the patient’s condition must be characterized by high precision and reliability in order to be able to detect even subtle progress detection or regression in the upper limb function. In this context, reliable measurements of grip strength and resistance force performed with the Biometrics E-link can be particularly useful for long-term therapy tracking and making clinical decisions regarding the further rehabilitation plan. Second, patients in the late stage often continue rehabilitation in the form of maintenance therapy or independent home exercises. In such cases, precise, repeatable measurements can be a valuable tool for objectively assessing the effectiveness of the applied measures, and thus support the individualization of the therapeutic process. Third, due to the more stable neurological condition of patients in the late post-stroke period, this phase provides ideal conditions for assessing the reliability of measurement tools. Minimal variability of motor functions over time allows for a more reliable assessment of test reliability, without the risk that any changes in the results will reflect spontaneous improvement or deterioration of the patient’s condition.

Moreover, the literature indicates that the use of reliable assessment tools does not consistently affect the choice and consensus on performance measures¹⁶. Prange-Lasonder et al. state that in order to plan an effective therapy program, it is necessary to use reliable, valid and available tools for clinical assessment of the upper limb in neurorehabilitation¹⁶. Our own study has shown that hand grip and pinch strength assessment performed using the Biometrics E-link assessment system demonstrate high test–retest reliability and inter-rater reliability, and therefore are a credible and reliable tool for clinical assessment of the hand in patients in the late period after stroke and can be successfully used in neurorehabilitation, and thus influence the consensus on outcome measures in the country and beyond.

Research indicates that Biometrics E-link is often used to assess hand grip and finger pinch strength in different populations of both patients with impaired hand function^9,10 and healthy individuals^5,8. Despite this, there is so far no research on assessing the reliability of this device in hand grip and pinch strength in the late stroke population. Germanotta et al. conducted a similar study, but it concerned the Amadeo device and people with subacute stroke¹⁷. The investigators assessed the reliability of a robotic device for finger training in 120 patients with subacute stroke, enrolled in 6 different rehabilitation centres. In contrast to our study, both people with first cerebral infarction and haemorrhage were included. We included only people with completed first ischemic stroke to ensure the homogeneity of the population. Germanotta et al. demonstrated that test–retest reliability was excellent for finger strength. Thus, as in our research, they confirmed that the results provided by the hand rehabilitation device under assessment are reliable and sensitive to measurement¹⁷. Bertrand et al. also assessed test–retest reliability of maximal grip strength measurements in a population in the first weeks after stroke, but using the Jamar device¹⁸. The authors showed high reliability of measurements made using the Jamar dynamometer in the population of people in the first weeks after stroke¹⁸. In the context of assessing hand function, it is also worth mentioning the GripAble tool. This is a device designed for both assessment and rehabilitation of hand grip strength, used mainly in neurology and orthopedics. Studies have shown that GripAble has high inter-rater and test–retest reliability, and at the same time offers the possibility of conducting interactive therapy in real time, which increases patient engagement and may improve rehabilitation results^19,20. Importantly, the latest studies emphasize the importance of determining the measurement properties of GripAble among the population of patients with upper limb dysfunctions, including stroke patients²¹. Thus, although our protocol did not include this tool, it fits into the broader context of the need to use integrated, reliable systems for assessing and treating hand function in neurorehabilitation.

It is also necessary to discuss the differences between Biometrics E-link and existing devices. Although the Jamar dynamometer is considered the gold standard for grip strength assessment, some clinicians consider it an outdated device because of its weight (weighs 680 g) and insensitivity to very small forces. There is a greater possibility of error in measurements because the Jamar dynamometer dial shows 2 kg and the needle on the dial jumps slightly, overestimating the actual reading^22,23. On the other hand, the Biometrics E-link, like the GripAble, is designed according to ASHT standards, providing high compliance with standardized normative data. It is a very sensitive and precise device. It gives handgrip strength results with an accuracy of less than 1%. Also, like the Jamar dynamometer, it gives results in kilograms and pounds. The Biometrics device can be used to assess handgrip strength, finger grip strength, muscle fatigue, and monitor therapy progress. It can be connected to other systems via an interface, which gives it an advantage over the Jamar and makes it a flexible diagnostic and therapeutic device. An additional advantage is the therapeutic use (use of interactive games with the biofeedback method) and the built-in E-Link software, with which we can perform analysis during the therapy. That is why we decided to use this device in our research. It is also worth adding that the Jamar Dynamometer and GripAble assess the strength of the hand grip without the possibility of assessing the strength of the fingers. Additionally, GripAble is a diagnostic and rehabilitation tool with the possibility of conducting therapy, just like Biometriocs, which is not available in the Jamar dynamometer. Amadeo, in turn, is a diagnostic and rehabilitation device for assessing muscle tone and spasticity, especially in the fingers²⁴. However, Amadeo, like Jamar and GripAble, do not assess finger grips, such as key, three jaw chuck, tip-to-tip, these are basic finger grips used in everyday functioning²⁵.

It is also worth adding that before we conducted an assessment of the reliability of Biometrics E-link device in hand grip and pinch strength in the late stroke population, we carried out the same assessment in the healthy population⁸. The study also confirmed high reliability in hand grip and pinch strength assessment among 122 healthy subjects⁸. Similar conclusions were also reached by other investigators, confirming the reliability of an electronic dynamometer for measuring grip strength, but in a much smaller population of 49 healthy people⁵. Also, research conducted by Dekkers et al. showed that the Biometrics E-link is a useful tool in grip and pinch strength measurements, but the study was conducted in a paediatric population with spastic cerebral palsy⁹. Kennedy et al., in turn, confirmed the excellent reliability of Biometrics E-link in grip strength assessment in a population of patients with rheumatoid arthritis¹⁰.

Moreover, it is worth emphasizing that in our analysis, SEM was assessed, which provides information about the precision of the measurement in the original units (kg), which is crucial for clinical interpretation. The obtained SEM values differed significantly depending on the tool used. For hand grip strength measurements with a dynamometer, SEM was about 1.30 kg. In contrast, all precision grip strength measurements performed with a pinchmeter were characterized by a significantly lower measurement error: for the key grip, SEM was about 0.37–0.41 kg, for the three-point grip about 0.37–0.39 kg, and for the fingertip grip about 0.28–0.30 kg. The SEM value has a direct impact on clinical practice. It can be used to calculate the Minimum Detectable Change (MDC), which determines how large the difference between two measurements must be to be able to say with confidence (usually 95%) that this is a real change and not a measurement error. For a dynamometer with an SEM of 1.30 kg, the MDC₉₅ (calculated as 1.96 × SEM) is approximately 2.55 kg. This means that only a change in grip strength exceeding 2.55 kg can be considered with 95% certainty as a real improvement or deterioration in the patient’s condition. The situation is completely different for finger strength measurements. With an SEM of approximately 0.4 kg (for a key grip), the MDC₉₅ is only approximately 0.78 kg. Such a low value of measurement error indicates the high precision of the pinchmeter and its ability to detect even small but real changes in the patient’s strength. Therefore, although the ICC coefficients were very high for all tools, the SEM values clearly indicate that the pinchmeter is a tool with higher absolute reliability.

Referring to the research by Bobos et al., in which a systematic review with meta-analysis was conducted in the field of measurement properties of the hand grip strength assessment, it can be concluded what values of deviations in measurements are acceptable, i.e. have clinical significance. The authors report differences of the order of 5 kg for the dominant side and 6.2 kg for the non-dominant side²⁶. Therefore, it can be stated that the results obtained by us are within the minimum clinically important difference (MCID). The measurements performed using the pinchmeter were characterized by high agreement in all analyzed variants, meeting the assumed criterion. All types of grips measured with the pinchmeter—key, three-point and fingertip—for both hands, showed good agreement both between the examiners and within the repetitions for one examiner. Comparing the results between Examiner 1 and Examiner 2, the width of the LoA range ranged from 3.444 (three-point grip, right hand, Study I) to 4.702 (fingertip grip, left hand, Study II). An even higher degree of precision was observed in the case of measurement repeatability (comparison of Study I vs. II for the same examiner). In these cases, the width of the LoA range was exceptionally low, often oscillating around the value of 1.0 or less. For example, for the right key grip, this width was only 0.878 for Researcher 1 and 0.758 for Researcher 2. In the case of the dynamometer, only the repeatability of measurements for the same researcher for the right hand was within the acceptable range. For Researcher 1, comparing his results from both studies, the width of the LoA interval was 3.984 with a mean difference (bias) of − 0.100. For Researcher 2, the corresponding width of the interval was even lower and amounted to 3.470, with a bias of − 0.235. We assume that the high quality of the results obtained with the pinchmeter may result from the simpler way of using this device, less involvement of large muscle groups, and less sensitivity to changes in the position of the patient’s body and hand. This may favor more consistent measurement conditions, which in turn translates into better reliability of the results.

To sum up the above considerations, the following implications for clinical practice were formulated: our research confirmed the clinical usefulness of the Biometrics E-link for hand grip and pinch strength assessment in patients in the late period after stroke, the analysis confirms that although both devices demonstrate excellent relative agreement, the pinchmeter is a much more precise instrument for monitoring the functional status of patients, which is crucial in assessing progress in neurorehabilitation. Moreover, based on our own experience and literature data²⁶ the results noted in our own studies may have a significant impact on the rehabilitation of patients in the late period after stroke in the clinical aspect. However, clinicians and researchers should pay attention to the position of the upper limb, the patient’s body position and their motivational strength when performing dynamometric measurement, which will reduce the risk of inter-individual errors. Therefore, we are planning further studies using the Biometrics E-link system to assess the effectiveness of therapy planning, progress monitoring, and home-base assessment in chronic stroke populations.

Limitations

The study has some limitations, the most important of which is that the assessment of upper limb hand grip and finger pinch strength using the Biometrics E-link was not supported by results obtained using scales and tests. However, we are planning further studies in which the effects of rehabilitation after a stroke will be assessed using the Biometrics E-link, as well as assessment scales and testing. Another limitation may be the age of patients over 50 years of age among whom the study was conducted. The criterion we took into account in terms of age is a risk factor that tells us that after the age of 50 the incidence of stroke increases, which is why we chose this age range. However, our research should also be extended to stroke survivors younger than 50 years of age, because the literature indicates that younger people increasingly often suffer strokes^27,28, what is more, the course of rehabilitation and response to interventions in younger groups of patients may be different. The research was conducted in a rehabilitation and spa hospital, where stroke survivors stay in the late period. Due to the more stable neurological condition of patients in the late period after stroke, this phase provides ideal conditions for assessing the reliability of measurement tools. Minimal variability of motor function over time allows for a more reliable assessment of test reliability, without the risk that any changes in results will reflect spontaneous improvement or deterioration of the patient’s condition, but future projects will also include stroke survivors in acute and subacute phases, because the reliability of Biometrics E-link assessments may vary during those phases of stroke when motor function variability may be greater.

Conclusions

The study showed that hand grip and pinch strength assessments performed using the Biometrics E-link assessment system demonstrate high test–retest reliability and inter-rater reliability. The Biometrics E-link can be recommended for daily clinical practice among people in the late period after stroke, however, the analysis showed that although both devices demonstrate excellent relative agreement, the pinchmeter is a much more accurate instrument for monitoring the functional status of patients, which is crucial in assessing rehabilitation progress.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Author contributions

J.L. conceived of the study and made substantial contributions to conception and design of the study, performed the statistical analysis, made the analysis and interpretation of data and drafted the manuscript. B.P. participated in the selection and medical care of the patients, coordination, data collection and interpretation. J.B. participated in the data collection, interpretation and performed the statistical analysis. A.G. participated in the design of the study, interpretation of data, drafting the manuscript and revising it critically forimportant intellectual content. All authors read and approved the final manuscript.

Funding

This research received no external funding.

Data availability

Data sharing statement: The datasets generated and/or analysed during the current study are not publicly available due to protect the patients privacy, but are available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare no competing interests.