Assessment of Hand Rehabilitation after Hand Surgery

by Means of a Sensory Glove

Giovanni Saggio

, Laura Sbernini

, Anna De Leo

, Mostafa Awaid

3,4

Nicola Di Lorenzo

and Achille L. Gaspari

Department of Electronic Engineering, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Rome, Italy

Plastic surgery department, John Radcliffe hospital, Oxford university hospitals, Oxford, U.K.

Department of Experimental Medicine and Surgery, University of Rome Tor Vergata,

Via Montpellier 1, 00133 Rome, Italy

Department of Biomedical Engineering, Higher Technological Institute, 10

of Ramadan City, 44135 Egypt

Keywords: Sensory Glove, Hand Rehabilitation, Range of Motion (ROM).

Abstract: The assessment of hand functions after hand surgery treatment is essential to address the optimal rehabilitation

procedures for any patient. To this aim, the current procedures anachronistically rely mainly on manual

goniometers (highly prone to human errors) and know-how of experienced medical staffs (potentially prone

to biased judgment), so that there is room for improvements in objective measurements of hand capabilities

and new technological systems are very welcome. In particular, systems based on sensory glove are gaining

more and more relevance in acquiring hand movement capabilities. Within this frame, in this research the

Range of Motion (ROM) for all fingers and the ability of participants (health vs. patient subjects) to repeat

two ADL (Activities of Daily Living)-based tasks were investigated. As a result, the glove-based system was

evaluated in its feasibility for the assessment of hand function in clinical practice and rehabilitation settings.

1 INTRODUCTION

Hands are fundamental for human body beings in a

huge number of tasks in our everyday life, for self-

caring, acting, expressing, signing etc. (Chen et al.,

2010). This is why, the correct measure of finger

movements can be fundamental in assessing deficits

after injuries of the central nervous system (Gentner

and Classen, 2009), and/or in evaluating the outcome

of hand surgery, so to dispense appropriate

rehabilitation strategies in restoring patients’ abilities

(Borghetti et al., 2013).

Joint range of motion (ROM) measurement is one

of the most important quantitative methods of hand-

function evaluation (Dipietro et al., 2003). Mechanical

goniometers or, more recently, potentiometric- and

electro- goniometers are traditionally used to measure

the passive ROM of each finger joint. The “small”

dimension of finger segments, compared to the

dimensions of the goniometers, makes difficult the

simultaneous measure of the entire finger ROMs

(Carpinella et al., 2006). Therefore, recently other

techniques have been considered, based on optical

technology, such as the analysis of digital

photographic images (Vergara et al., 2003) and the

multi-camera photogrammetry (Lee and Rim, 1991).

These solutions represent improvements, but are

limited only to static measurements. Dynamic and

simultaneous measures are allowed by an

optoelectronic analysis, but the necessary optical

markers are prone to problems of occlusion, low

ambient illumination can affect the result, and the high

equipment cost do not favor their clinical acceptance.

Systems based on sensory glove can represent an

interesting alternative within this frame; this is why

we intend to evaluate their feasibility (Saggio et al.,

2014). Data recorded by means of a sensory glove can

even furnish the possibility to drive an avatar of the

hand, so to replicate the hand movements for further

analysis (Saggio et al., 2009).

By means of a custom made sensory glove, we

investigated all joint finger ROMs, and the ability of

healthy and patient subjects to repeat gestures in

performing two easy grasping tasks.

Saggio, G., Sbernini, L., Leo, A., Awaid, M., Lorenzo, N. and Gaspari, A.

Assessment of Hand Rehabilitation after Hand Surgery by Means of a Sensory Glove.

DOI: 10.5220/0005704201870194

In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016) - Volume 1: BIODEVICES, pages 187-194

ISBN: 978-989-758-170-0

187

2 MATERIALS AND METHODS

2.1 Sensory Glove

Typically, a sensory glove is a cloth glove equipped

with flex sensors (Saggio, 2012). It was proposed for

semi-automated goniometry in order to address the

shortcomings of passive measures and to explore

functional activities (Dipietro et al., 2003; Williams et

al., 2000). Different types of sensory glove have been

proposed, both commercial and research ones.

To best fit our requirements, we developed two

twin indigenously-made sensory gloves (small and

medium sized), equipped with 14 resistive flex sensors

(by Flexpoint Sensor Systems, Inc., Draper, UT)

placed in correspondence of the interphalangeal (IP)

and metacarpophalangeal (MCP) joints of the thumb,

and distal interphalangeal (DIP), proximal

interphalangeal (PIP) and metacarpophalangeal (MCP)

joints, to trace finger flex/extension movements (see

Figure 1). When a sensor is bent, its resistance value

increase proportionally to the bending angle (Saggio,

in press).

Analog signals from the glove fed an ad-hoc

realized electronic circuitry, which send processed

data to a personal computer moving a hand avatar

according to the measures.

2.2 Participants

A group of 11 subjects without hand abnormalities, 9

healthy (6 women and 3 men) averaging 26 years in

age (range 24-32y) and 2 patients (2 women, 17 and

65y respectively), performed the tests. Patient #1

(17y) underwent left hand surgery after an incision

injury for MCP joint of the index finger. Patient #2

(65y) underwent left hand surgery because of carpal

tunnel syndrome and trigger finger (middle finger).

2.3 Experiment Set-up and Test

Protocol

The experiment was divided into three tests termed A,

B, C (detailed in the following), which requested to

place the hand recursively in known positions, with

the glove always kept.

Before each test, the subjects were asked to sit on

a chair in front of a table, the arm and forearm forming

90°. The hand in flat position and the wrist in neutral

position defined the reference for each of the joints at

0°.

The subject donned his/her best fitting sensory

glove (medium or small size) above a latex one.

He/she was then trained to the testing procedures, as

Figure 1: The sensory glove prototype and the experimental

materials.

follows:



Test A Open-Close: the subject placed his/her

elbow joint on the table-top and was asked to

completely open his/her hand (angle of 0°,

without hyperextension) and then completely

close it (the thumb above the fingers).



Test B Grasping Bottle (Transverse Volar Grip):

it started with the hand in flat position. The

subject was asked to grasp (using all fingers), and

to release a spray bottle (diameter 2.5cm, height

15cm, see Figure 1). He/she returned then to the

initial neutral position.

 Test C Grasping Dressing Roll (Five-Finger

Pinch): Test C was analogous to Test B, but a

dressing roll (diameter 4.5cm, height 7cm) was

used instead of the bottle.

The bottle and the roll grasps were adopted based

on the most daily used hand-grips (Sollerman, 1995),

and objects’ neutral positions were drawn on the

table-top. No time constraints were given during all

the experiments.

For repeatability evaluation, the subjects

performed each task five times without removing the

glove. For reproducibility evaluation, the subjects

performed again the overall procedure two weeks

after (so that the glove was doffed and donned

between days). For each repetition of each task, data

of all sensors were acquired during the entire

performance: from the starting position to the ending

position of the hand.

Healthy subjects performed the tests by using both

left and right hand; patients performed the tests only

with the injured hand. During the two weeks between

tests, patients followed a rehabilitation program

(extracorporeal shockwave therapy), therefore data

analysis can focus on the assessment of rehabilitation

outcomes.

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2.4 Data Processing

An ad-hoc circuitry was designed to acquire data from

sensors and to condition the signals (resistance values

were converted into voltages and analog values into

digital ones), before transmitting them to a personal

computer, which converted incoming data into

original angles for further analysis.

Test A: Angle data was processed obtaining the

average ROM (maximum angle – minimum angle) for

each finger joints. Repeatability of the measures was

assessed considering standard deviation (SD) values.

Test B and C: The repeatability among dynamic

measures was assessed considering the intra-class

correlation coefficient (ICC) (Shrout and Fleiss,

1979), close to 1 for a high reliability, close to 0 for

low reliability. For each measure, the dynamic angle

values were time-normalized, so to calculate the ICC

coefficients comparing curves with the same number

of samples.

2.5 Statistical Analysis

For each day and for each healthy subject, we obtained

a reference value of the entire hand for the two

parameters of repeatability, SD of ROM (Test A) and

ICC coefficient (Test B and C). We calculated the

mean value across all finger joints and a statistical

analysis was performed using these results. An

ANOVA for repeated measures with two within-

subjects factors was conducted to assess if time and

handedness (and their interaction) might influence

measurements repeatability. The level of significance

was set at 0.05.

2.6 User Interface

We developed a useful graphical user interface (GUI)

to facilitate usability of our system by clinicians

(Figure 2). The GUI allowed selecting the joint of

interest that the clinician wants to evidence. Also, it

allowed calculating the repeatability of each

Figure 2: System Graphical User Interface (GUI).

sensor/joint during dynamic tasks.

All data processing was performed using Matlab

(MATLAB R2013a, The MathWorks, Inc., Natick,

MA) programs.

2.7 User Feedback Questionnaire

Feedback regarding comfort with handling and

wearing the glove was assessed by a user

questionnaire (Table 1) adapted from (Gentner and

Classen, 2009; Simone, 2007). For each item, subjects

were asked to select one of seven statements from 1

(strongly disagree) to 7 (strongly agree). Item Q12 was

administered only to healthy subjects.

3 RESULTS AND DISCUSSIONS

3.1 Test a: Healthy Subjects

The mean ROM values and their SDs among all the

healthy subjects are shown in Figure 3a,b separately

for each joint. Repeatability of ROM is reported as

standard deviation and all joints showed comparable

SD values. SD for right hand range from 0.36° to 2.93°

(mean value 1.60°) and from 0.92° to 8.49° (mean

value 2.97°) for first and second day respectively; SD

for left hand range from 0.66° to 9.84° (mean value

2.67°) and 1.35° to 5.96° (mean value 3.09°) for first

and second day respectively.

3.2 Test B and C: Healthy Subjects

ICC analysis was performed for Test B and Test C

individually, and for each sensor. For healthy subjects,

the average values of ICC for each joint are shown in

Figure 4a,b.

For Test B, the average ICC across all the fingers

in the two days is 0.76 for the right hand and 0.79 for

the left one. For Test C, the average ICC across all the

fingers in the two days is 0.85 for the right hand and

0.83 for the left one.

The obtained ICC values were consistent with no

particular joint showing markedly lower repeatability

than the mean. Overall, repeatability was

quantitatively assessed by ICC mean values ranging

from 0.74 to 0.89 with a mean across joints of 0.81.

These results were comparable to the ones obtained

with the gloves evaluated by Simone et al. (Simone,

2007) (ICCs from 0.79 to 0.99 with a mean of 0.95),

Dipietro et al., (2003) (ICCs from 0.7 to 1.0), and

Mentzel et al., (, 2001) (ICCs from 0.82 to 0.99, with

a mean of 0.94).

The repeatability and reliability of our sensory

Assessment of Hand Rehabilitation after Hand Surgery by Means of a Sensory Glove

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Table 1: User feedback questionnaire*

Q# Question

Q1 I felt comfortable as the glove was put on

Q2 I did not feel like my fingers were put into any uncomfortable position as the glove was put on

Q3 I felt any restriction to movement with this glove

Q4 I felt comfortable performing the activities in this study

Q5 The glove did not feel too tight (it did not make my hands or fingers tingle)

Q6 I feel like I can bend my fingers just like I can without wearing the glove

Q7 The glove did not feel too hot or too cold

Q8 I did not feel a reduction in tactile sensitivity of the fingers with this glove

Q9 I had no trouble during the grasping tasks wearing this glove

Q10 I did not feel like my fingers were put into any uncomfortable position as the glove was removed

Q11 I felt comfortable as the glove was removed

Q12 I did not felt any difference when I was worn the left glove

* Answers were coded as: 1 = strongly disagree, 2 = disagree, 3 = somewhat disagree, 4 = neutral, 5 =

somewhat agree, 6 = agree, and 7 = strongly agree.

Adapted from (Gentner and Classen, 2009; Simone, 2007).

glove is similar to other evaluated gloves and also lies

within the measurement reliability of manual

goniometry. This result shows both the reliability of

the used system and the ability of the healthy

participants to repeat the same gesture. These results

allowed us to use the system for further analyses with

patient subjects.

3.3 Statistical Analysis

Statistical analysis showed that time and the

interaction between time and handedness did not

influence standard deviation of ROM values

(respectively p = 0.644 and p = 0.612). On the contrary,

there were significant differences (p = 0.042)

comparing SD data between right and left hand.

For the dynamic repeatability of Test B and Test C,

the statistical analysis was conducted across the ICC

coefficients of the healthy subjects. It showed that

time, handedness and their interaction did not

influence repeatability of Test B (time p = 0.868;

handedness p = 0.295; time*handedness p = 0.234).

For Test C, the statistical analysis showed that time

might influence dynamic repeatability of grasping a

dressing roll (p = 0.002). On the contrary there were

not significant differences due to the dominance of the

hands (p = 0.381). The interaction between time and

handedness did not present statistical differences (p =

0.258).

These results suggest that further investigations

are welcome because of the two significance

outcomes: handedness for the SD of the ROM (p =

0.042 ≈ 0.05) and time for Test C. Grasping a dressing

roll (Test C) might be a gesture not easy to repeat

similarly between two days of measurements because

even a healthy subject gets familiar with the gesture.

3.4 Feasibility Evaluation with Patient

Subjects’ Data

Patient subjects’ results of the ROM (mean ± SD) (see

Figure 3c,d individually for the two participants)

demonstrate how the ROM has changed after two

weeks of rehabilitation.

It is worth to investigate ROM results for the main

joints involved in surgery. For patient #1 (left hand

surgery after an incision injury for MCP joint of the

index finger) values of the ROM of index joints

markedly increase between days: MCP joint range

19.3÷77.3°; PIP joint range 53.1÷136.3°; DIP joint

range 30.4÷63.9°. For patient #2 (middle finger joints

surgery), values of the ROM of middle finger remain

quite unchanged between days: MCP joint range

47.2÷48.3°; PIP joint range 32.3÷37.7°; DIP joint

range 6.8÷9.6°. Patient subjects’ outcome suggests

that motor recovery for patient #1 was quicker than for

patient #2. Actually, the former had easily recovered

hand function abilities while the latter showed a slow

recovery.

The average values of ICC of Test B and Test C for

left hand joints of patient subjects are shown in Figure

4c,d. For Test B, the average ICC across all the fingers

between days is 0.71 for the first patient and 0.56 for

the second one. For Test C, the average ICC across all

the fingers in the two days is 0.65 for the first patient

and 0.82 for the second one. For the first patient, there

was not an increase of the overall ICC values between

the days of measurements, while there was a marked

increment for the second patient. These results suggest

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(a) (c)

(b) (d)

Figure 3: Range of Motion (ROM) values: for healthy subjects (a) right hand and (b) left hand; for patient subjects (c) Patient

#1 and (d) Patient #2. Results are presented as mean value and standard deviation separately for each day of measurements.

For each group of joints (MCP, PIP and DIP), fingers are coded as follows: 1 = thumb, 2 = index, 3 = middle, 4 = ring and 5

= small finger.

Assessment of Hand Rehabilitation after Hand Surgery by Means of a Sensory Glove

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to assess specific tasks for different hand injuries.

Repeatability was quantitatively assessed by ICCs

ranging from 0.64 to 0.74 with a mean across joints of

0.68 for the first patient, and ranging from 0.41 to 0.89

with a mean across joints of 0.69 for the second

patient. Comparing with the results in Figure 4a,b,

ICC values of patients are lower than the mean values

of ICC of the healthy subjects as we expected.

3.5 User Feedback Questionnaire

The questionnaire gave positive responses to most

questions: the average scores across all subjects are

between 4.0 and 7.0 and between 5.0 and 7.0 out of a

maximum score of 7 respectively for the first and

second day (see Table 2). Average responses for all

subjects were positive, the mean and SD being 5.82±

0.60 and 6.09 ± 0.28 for first and second day

respectively. Responses were not significantly

different between the healthy group and the patient

group, so results are shown as average values across

all subjects. Questions 1, 2, 10 and 11 addressed

comfort during donning and doffing the glove and the

average responses for all subjects were positive: 6.08

±0.25 and 6.12±0.06 for the first and the second day

respectively. Questions 3, 4, 5, 6, 7, 8, 9, and 12

captured feedback about the comfort performing the

ADL-based activities wearing the glove and the

positive average responses for all subjects reported a

significant goal: 5.78±0.43 and 6.07±0.26 for first

and second day respectively.

The average responses for all subjects for the

second day is better than ones for the first day

supposedly because of the subjects are being familiar

with using the glove. From a general point of view the

participants reported comfort with the glove and no

relevant obstruction in movements.

4 CONCLUSIONS

The aim of this research was to furnish to the

clinicians a system for measuring finger joints

movement that is accurate, objective, easy to use and

that delivers useful data through an easy user interface.

It focused on the human finger postures and dynamic

function movements during the accomplishment of

ADL-based tasks rather than on the ability to

accomplish these tasks. Furthermore, the proposed

system allows tracking the movements of finger joints

by means of virtual reality during a rehabilitation

plane.

Our system is very easy to use, it can be used in

many applications (e.g. evaluation of patient motor

therapy and rehabilitation process), it can capture

dynamically the full range of motion during finger-

joint bending and it can monitor all the joints of one

finger. Its performances are comparable to ones of

other evaluated gloves, confirming the feasibility of

the system, but to our knowledge, there are not other

examples of applications of sensory gloves to assess

hand surgery follow-up.

Table 2: User feedback questionnaire: mean scores per question.

Healthy Subjects (N=9) Patient Subjects (N=2) All Subjects

Day 1 Day 2 Day 1 Day 2 Day 1 Day 2

Q1 6.0 6.2 5.0 6.0 5.0 6.2

Q2 5.8 6.1 6.0 6.5 5.0 6.3

Q3 5.3 5.7 4.5 6.0 5.0 5.9

Q4 6.3 6.2 6.0 6.0 6.2 6.1

Q5 6.2 6.2 7.0 6.5 6.6 6.4

Q6 5.4 5.9 6.5 6.0 6.0 6.0

Q7 6.0 6.2 7.0 6.0 6.5 6.1

Q8 5.3 5.8 5.0 6.5 5.2 6.2

Q9 6.1 6.1 6.0 6.5 6.1 6.3

Q10 6.3 6.2 4.0 5.0 5.2 5.6

Q11 6.2 6.1 7.0 7.0 6.6 6.6

Q12 5.4 6.4 - - 5.4 6.4

Total 5.9±0.4 6.1±0.2 5.8±1.1 5.7±1.9 5.7±0.7 6.2±0.3

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(a) (c)

(b) (d)

Figure 4: Mean values of Intra-class Correlation Coefficients (ICCs): healthy subjects Test B (a) and Test C (b); patient

subjects Test B (c) and Test C (d). For healthy subjects results are shown separately for the right and the left hand. For each

group of joints (MCP, PIP and DIP), fingers are coded as follows: 1 = thumb, 2 = index, 3 = middle, 4 = ring and 5 = small

finger. Pt_1: patient subject #1; Pt_2: patient subject #2.

Assessment of Hand Rehabilitation after Hand Surgery by Means of a Sensory Glove

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Through analyzing tasks of healthy subjects, we

were able to study characteristics of the ROM of the

finger joints and movement repeatability. The results

of healthy subjects’ tests might serve as standard

values and help us in evaluating the severity of a

hand functional deficit in the future.

This work presents the preliminary outcomes of

our research, and its positive results encourage

further studies aiming at confirming the present

finding and fostering the proposed system into

clinical practice. Our next steps will be to examine

more patient subjects after hand surgery, to compare

between them, to assess the rehabilitation process

and correspondingly improve the efficiency of

rehabilitation.

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