The eligibility criteria for the young participants included in the study were 20 ≤ age < 30 years and were affiliated with the Faculty of Nursing and Welfare, the Kyushu University of Nursing and Social Welfare, in Japan. The exclusion criteria included having an experience of carrying out tasks similar to those required to be performed for this study or having a current or past (history of) orthopaedic or neurological disease of the hands and fingers that impacted ADL. The eligibility criteria for elderly individuals were age ≥ 65 years, those living in their own homes (main place of residence), and able to ambulate without a walking aid, and able to travel to the study venue by themselves. The exclusion criteria for the latter group were having an experience of carrying out tasks similar to those required for this study, having a current or past (history of) an orthopaedic or neurological disease of the hands and fingers that impacted ADL, or scoring ≤ 23 on the Mini-Mental State Examination.
A power analysis was conducted to estimate the sample size using G*Power 188.8.131.52. The sample size calculation was considered as a power calculation to detect differences between the groups in the performance of a task that required AGF during the test sessions. We used repeated measured analysis of variance (ANOVA), within-between interaction with an α error level probability of 0.05, and a power (1-β error probability) of 80%. The medium effect size Cohen was set to f = 0.25. The analysis described above revealed that a total sample size of 34 was required for this study. Therefore, recruitment was closed when 17 applicants from each group were confirmed. As a result, 36 healthy individuals (28 men and 8 women) participated in this study. The participants were divided into two age groups. The young group (14 women, 4 men) were aged between 20 and 22 years (mean age = 21, SD = 0.3) and the elderly group (14 women, 4 men) were aged between 60 and 75 years (mean age = 71, SD = 3.9).
None of the participants reported any neurological or vestibular disorders or orthopaedic conditions before participating in the study. The participants had no prior experience with the learning task, and they were not informed of the specific purpose of our study. A preliminary explanation of the study details was provided to all participants, and written consent was obtained. Our study protocol was approved by the Institutional Review Board of Kobe International University (G2019-102). A preliminary explanation of the study details was provided to all participants, and written informed consent was obtained. All procedures were approved by the institutional review board and performed in accordance with the Declaration of Helsinki.
Equipment and tasks
In this study, iWakka (Aimu Co., Ltd.) was used to measure AGF based on a report by Kaneno[1, 2] (Fig. 1). Written informed consent for publication of an image of Fig. 1 was obtained from one of the authors. iWakka is a cylindrical device with a height of 80 mm and a diameter of 65 mm and can measure a grasping force of 0–400 g depending on the degree of opening and closing of the device. During the measurement, the subject held the iWakka in a sitting position with one hand and continuously adjusted the grasping force to approximate an arbitrarily set target value. The measured value and the target value during measurement can be displayed as feedback on a monitor placed in front of the participant. Since the AGF is calculated as the root mean square error (RMSE) from the absolute error per unit time between the measured value and the target value, a smaller absolute value is indicative of a better AGF.
Two AGF tasks were used in the study. First, a 100g AGF task was set as an index of difference between the desired and actual performance in the state, excluding the visual information and the temporal aspect. In this task, the participant was asked to adjust the measurement value of iWakka to 100g for 10s without looking at the monitor. Next, the main learning task was set as a task to be learned through practice. In this task, the participants were asked to continuously adjust their grasping force to match the target values, as shown in Fig. 2. The task consisted of 30 seconds per trial.
In this study, referring to the report by Cuthbertson et al., visual reaction time (VRT) was measured as an index reflecting visual-motor speed using the website www.humanbenchmark.com. We performed this task using a computer that could connect to the Internet. The participants were asked to click the mouse as soon as possible when the colour of the front screen automatically changed from red to green. The time (milliseconds) from when the screen turns green to when the participant clicks the mouse is automatically calculated.
The elderly and young groups were measured for 2 days using the same procedure (Fig. 3). Prior to the measurement, the dominant hand of each participant was determined using the Edinburgh Handedness Scale. In this study, the learners performed all the tasks with their non-dominant hands. As a result of the Edinburgh Handedness Scale, all the participants were right-handed, so they performed the task with their left hand.
After determining the dominant hand, the 100g AGF task was measured five times. No feedback was given to prevent the participant from correcting the difference between the desired performance and actual performance. After the completion of the 100g AGF task, the visual simple reaction time was measured five times.
Subsequently, the participants performed a pre-test, acquisition phase, and retention test of the main learning task. In the pre-test, the participants performed four trials of the task without feedback. The acquisition phase consisted of three blocks with one block in four trials. Subsequently, the participants performed a total of 12 trials. During the acquisition phase, the participant was given concurrent feedback by confirming the target value and the actual measured value displayed on the monitor. A 20-second break was set between each trial, and a 60-second break was set between each block. The retention test was conducted 24h after completion of the acquisition phase with similar contents to the pre-test.
Outcome measures and statistical analysis
In this study, the RMSE of the 100g AGF task and the main learning task were used as parameters of the AGF. For the 100g AGF task, the RMSE was calculated from the target value and the measured value with 5 to 10s of the measurement time as the analysis range, and the average value of five trials was calculated. Next, in the main learning task, the RMSE was calculated with a measurement time of 5 to 30s as the analysis range, and the average value was calculated in the pre-test, each block of the acquisition phase, and the retention test.
Statistical analyses were conducted using IBM SPSS Statistics 25 (IBM Corp., NY, USA) for Windows. The design for the analysis of the test and acquisition data was a 2×2 (generation × test) ANOVA with repeated measures on the last factor. When a significant main effect or interaction was obtained, the paired sample t-test and the independent sample t-test were performed as post hoc tests. Independent sample t-tests were also performed on the 100g AGF task and VRT in the elderly and young groups.
In addition, to examine factors related to motor learning of the tasks that require AGF, a multivariable linear regression analysis using the stepwise method was performed for all participants. The analysis used the RMSE of the retention test as the objective variable, the age, and the RMSE of the pretest as the explanatory variables. Furthermore, to analyse the difference between desired performance and actual performance and the effect of visual-motor speed on performance during the acquisition phase, a multivariable linear regression analysis was performed on each group of participants. In this analysis, a stepwise method was used with the RMSE of each block in the acquisition phase as the objective variable and the 100g AGF task and VRT as the explanatory variables. Statistical significance was set at p < 0.05.