CN104027225B - A kind of road conditions recognition methods - Google Patents

Abstract

The invention discloses a road condition identification method for lower limb rehabilitation aids. The road condition identification method is to install a heel sensor module on the heel of the foot tissue, install a toe sensor module on the toe of the foot tissue, and install a gyroscope module on the calf tissue. The control module processes the information of each sensor, and according to the information extracted by the sensor, after comprehensive analysis, it realizes the effective identification of different road conditions during the movement of the lower limbs of the human body. According to different road conditions, the drive module is used to control the lower limb rehabilitation aids to make corresponding actions, so that the lower limb rehabilitation aids and the wearer can truly reach the same pace, so that they can easily complete daily activities such as climbing stairs, climbing slopes, and crossing obstacles.

Description

A road condition recognition method

technical field

The invention relates to the technology of human lower limb rehabilitation aids, specifically a road condition identification method, which can identify six different road conditions of flat ground/uphill/downhill/upstairs/down stairs/obstacles, and then carry out corresponding rehabilitation aids. The control, while reducing the burden on the patient, makes the patient safer during walking.

Background technique

At present, lower limb rehabilitation aids play a vital role in the disabled population. Lower limb rehabilitation aids are mainly divided into two categories, one is rehabilitation aids for wearers with impaired lower limbs, and the other is lower limb rehabilitation aids. A rehabilitation aid for able-bodied wearers. Lower limb rehabilitation aids for wearers with physical disabilities, typically such as artificial limbs, etc., the types of artificial limbs currently entering the market, starting with "passive" artificial limbs, such as simple mechanical devices, linkages (mostly four-bar linkages) ), pneumatic or hydraulic devices, and computer intelligent control devices, and later invented "active" prosthetics with added power devices. In particular, "active" prosthetics can provide effective power that "passive" prosthetics cannot provide for the wearer during movements such as going up and down stairs and climbing slopes. However, the focus of these technologies is on the mechanism design and control of the prosthetic knee joint, aiming to reduce the fatigue of the disabled during walking. However, the detection technology and identification method of external road condition information such as stairs and slopes are rarely mentioned. . Similarly, rehabilitation aids for wearers with healthy limbs, such as exoskeletons, also involve the problem of road condition recognition methods.

Contents of the invention

Aiming at the deficiencies of the prior art, the present invention proposes: a road condition recognition method. This method is mainly used for lower limb rehabilitation aids, which can identify six common road conditions during walking, and provide control signals for driving lower limb rehabilitation aids, thereby helping disabled people solve problems encountered in road conditions such as climbing stairs and climbing slopes.

The technical solution of the present invention to solve the road condition recognition problem is to design a road condition recognition method. The hardware structure adopted by the road condition recognition method comprises a heel sensor module, a toe sensor module, a gyroscope module, a control module, a drive module, a lower limb rehabilitation aid knee joint, a calf tissue and a foot tissue; the heel sensor module, the toe sensor module Installed on the heel and toe of the foot tissue respectively, the gyroscope module is installed in front of the calf tissue, between the knee joint and the foot tissue of the lower limb rehabilitation aid; the control module is installed on the knee joint and the calf tissue of the lower limb rehabilitation aid The position below the drive module and the top of the gyroscope module; the drive module is installed at the upper position between the knee joint and the calf tissue of the lower limb rehabilitation aid. The heel sensor module, toe sensor module, and gyroscope module are all electrically connected to the control module; one end of the drive module is electrically connected to the control module, and the other end is electrically connected to the knee joint of the lower limb rehabilitation aid.

The road condition identification method is specifically as follows:

1). Selection of special points of angular velocity signal

The signal collected by the gyroscope module is input to the control module, and after being processed by the control module, the angular velocity signal of the back and forth swing of the calf tissue is obtained; the gyroscope module detects a signal of a gait cycle, and determines a gait cycle The three special points of the medium angular velocity signal are used as the basis for the heel sensor module and the toe sensor module to distinguish the road conditions. The three special points are: the starting point of the periodic signal, the minimum point of the transition from the first waveform to the second waveform of the periodic signal , the peak point of the second peak of the periodic signal;

2). Specific identification process of six road conditions

(1) When the signal detected by the gyroscope module is at the starting point, judge whether the toe sensor module detects a foreign object or occlusion; if the toe sensor module detects a foreign object or occlusion, it may be an obstacle/uphill/stairs Road conditions (referred to as mode 1), the control module regulates the driving module to control the lower limb rehabilitation aids to raise the legs; if the toe sensor module does not detect foreign objects or obstructions, it may be flat ground/downhill/down stairs (referred to as mode 2) three road conditions ;Therefore, at the starting point, the current road conditions can be divided into two categories: mode 1 and mode 2;

(2) When the gyroscope module detects that the signal reaches the minimum point, it judges the three road conditions of mode 1. If the heel sensor module detects that there is a foreign object or occlusion behind the foot tissue, the road condition is an obstacle; If the sensor module does not detect any foreign objects or occlusions behind the foot tissue, it is two road conditions of going up stairs/uphill (mode 3 for short); at the same time, it judges the three road conditions of mode 2, if the heel sensor module does not detect foreign objects or If it is blocked, the road condition is flat; if the heel sensor module detects a foreign object or occlusion, it is two kinds of road conditions: down stairs/downhill (referred to as mode 4); thus, the road condition is further divided into obstacles and flat ground at the minimum value point. , mode 3 and mode 4 four road conditions;

(3) When the signal measured by the gyroscope module reaches the peak point, use the toe sensor module to distinguish the two road conditions of mode 3. If the toe sensor module detects foreign objects or obstructions, the road condition is going up stairs; if the toe sensor module If no foreign object or occlusion is detected, the road condition is uphill; at the same time, the toe sensor module is used to distinguish the two road conditions of mode 4. If the toe sensor module detects foreign objects or occlusion, the road condition is down stairs; if the toe sensor module does not If a foreign object or occlusion is detected, the road condition is downhill; thus, at the peak point, the road condition can be further divided into six road conditions: flat ground/uphill/downhill/up stairs/down stairs/obstacles.

Compared with the prior art, the road condition recognition method pertinently subdivides the six road conditions existing in real life, and overcomes the defect that the prior art lacks a timely road condition recognition method. With this road condition recognition method, the lower limb rehabilitation aids can timely and accurately identify the six road conditions of flat ground/uphill/downhill/upstairs/downstairs/obstacles, so that the judgment of the lower limb rehabilitation aids on the road conditions can be compared with the lower limb rehabilitation aids. The judgment of the wearer is consistent, and with the control module and the drive module, the lower limb rehabilitation aids and the wearer can truly reach the same pace, so that they can easily complete daily activities such as climbing stairs, climbing slopes, and crossing obstacles, improving their quality of life and making them Better integrate into society and carry out normal life.

Description of drawings

Fig. 1 is a schematic diagram of hardware part installation of an embodiment of the road condition recognition method of the present invention applied to wearers with disabled lower limbs;

Fig. 2 is a schematic diagram of the installation of the hardware part of an embodiment of the road condition recognition method of the present invention for a wearer with healthy lower limbs;

Fig. 3 is a trend diagram of a gait cycle signal of a gyroscope module of an embodiment of the road condition recognition method of the present invention;

FIG. 4 is a flow chart of road condition recognition in an embodiment of the road condition recognition method of the present invention.

Specific implementation method

The present invention will be further described below in conjunction with the embodiments and accompanying drawings, but the present invention is not limited to the present embodiments.

The road condition recognition method of the present invention is characterized in that the hardware structure adopted by the road condition recognition method includes a heel sensor module 1, a toe sensor module 2, a gyroscope module 3, a control module 4, a drive module 5, a lower limb rehabilitation aid knee joint, and a calf tissue and foot tissue; the heel sensor module 1 and toe sensor module 2 are respectively installed on the heel and toe of the foot tissue, and the gyroscope module 3 is installed directly in front of the calf tissue, located at the knee joint and foot tissue of the lower limb rehabilitation aid In the middle; the control module 4 is installed at the position below the drive module 4 between the knee joint and the calf tissue of the lower limb rehabilitation aid, above the gyroscope module 3; the drive module 4 is installed between the knee joint and the calf of the lower limb rehabilitation aid The upper position between the tissues; the heel sensor module 1, the toe sensor module 2, and the gyroscope module 3 are all connected to the control module 4 respectively; one end of the drive module 4 is electrically connected to the control module 5, and the other end is connected to the lower limb rehabilitation The assistive knee joint is electrically connected.

Example 1

A lower extremity assistive device for wearers with lower extremity impairments (see Figure 1).

The hardware structure used comprises a heel sensor module 1, a toe sensor module 2, a gyroscope module 3, a control module 4, a drive module 5, a prosthetic knee joint 61, a lower limb auxiliary device calf 71 and a lower limb auxiliary device prosthetic foot 81; the heel sensor module 1. The toe sensor module 2 is respectively installed on the heel and toe of the lower limb auxiliary device prosthetic foot 81, and the gyroscope module 3 is installed directly in front of the lower limb auxiliary device calf 71, between the prosthetic knee joint 61 and the lower limb auxiliary device prosthetic foot 81; The control module 4 is installed at the position below the driving module 5 between the prosthetic knee joint 61 and the lower limb auxiliary device calf 71, and above the gyro module 3; the driving module 3 is installed between the prosthetic knee joint 61 and the lower limb auxiliary device calf 71 The upper position between; the heel sensor module 1, the toe sensor module 2, and the gyroscope module 3 are all electrically connected to the control module 4; one end of the drive module 5 is electrically connected to the control module 4, and the other end is electrically connected to the prosthetic knee joint 61 electrical connection.

Example 2

A lower extremity assistive device for wearers with able-bodied lower extremities (see Figure 2).

The used hardware structure comprises a heel sensor module 1, a toe sensor module 2, a gyroscope module 3, a control module 4, a drive module 5, a knee joint auxiliary device 62, a wearer's calf 72, a wearer's foot 82 and a bandage 9; The sensor module 1 and the toe sensor module 2 are respectively installed on the heel and the toe of the wearer's foot 82; the knee joint aid 62 is installed on the wearer's knee joint; the gyroscope module 3, the control module 4 and the driving module 5. Fix the bandage 9 directly in front of the wearer's calf 72, between the knee joint aid 62 and the wearer's foot 82; Electrical connection; one end of the drive module 5 is electrically connected to the control module 4 , and the other end is electrically connected to the knee joint aid 62 .

The road condition identification method is specifically as follows:

1). Selection of special points of angular velocity signal

The signal collected by the gyroscope module 3 is input to the control module 4, and after being processed by the control module 4, the angular velocity signal of the back and forth swing of the calf tissue is obtained. The gyroscope module 3 detects the signal of a gait cycle (see Figure 3), and determines three special points of the angular velocity signal in a gait cycle as the basis for the heel sensor module 1 and the toe sensor module 2 to distinguish road conditions. The three special points In order: the starting point of the periodic signal ①, the minimum point of the transition from the first waveform of the periodic signal to the second waveform ②, and the peak point of the second peak of the periodic signal ③.

2). The specific identification process of six road conditions (see Figure 4)

(1) When the signal detected by the gyroscope module 3 is at the special point ①, it is judged whether the toe sensor module 2 detects a foreign object or an obstruction. If the toe sensor module 2 detects a foreign object or occlusion, it may be three road conditions of obstacles/uphill/stairs (referred to as mode 1), and the control module 4 regulates the driving module 5 to control the lower limb assisting device to raise the leg; if the toe sensor If module 2 does not detect foreign objects or occlusions, there may be three road conditions: flat ground/downhill/down stairs (mode 2 for short). Therefore, in the special point ①, the current road conditions can be divided into two categories: mode 1 and mode 2.

(2) When the gyroscope module 3 detects that the signal reaches the special point ②, the three road conditions of mode 1 are judged. If the heel sensor module 2 detects that there is a foreign object or occlusion behind the foot tissue, the road condition is an obstacle; if If the heel sensor module 2 does not detect that there are foreign objects or occlusions behind the foot tissue, it is two road conditions of going up stairs/uphill (mode 3 for short). At the same time, the three road conditions of mode 2 are judged. If the heel sensor module 1 does not detect foreign objects or occlusions, the road conditions are flat; Referred to as mode 4). Therefore, in the special point ②, the road conditions are further divided into four types: obstacles, flat ground, mode 3 and mode 4.

(3) When the signal measured by the gyroscope module 3 reaches the special point ③, use the toe sensor module 2 to distinguish the two road conditions of mode 3, if the toe sensor module 2 detects foreign objects or blocks, the road condition is going up stairs; If the toe sensor module 2 does not detect foreign objects or occlusions, the road condition is uphill. At the same time, use the toe sensor module 1 to distinguish the two road conditions of mode 4. If the toe sensor module 1 detects a foreign object or occlusion, the road condition is down stairs; if the toe sensor module 1 does not detect a foreign object or occlusion, the road condition is down. slope. Therefore, in the special point ③, the road conditions can be further divided into six types of road conditions: flat ground/uphill/downhill/up stairs/down stairs/obstacles.

Thus, using the three special points of the gyroscope module 3 to cooperate with the heel sensor module 1 and the toe sensor module 2, six road conditions of flat ground/uphill/uphill/up stairs/down stairs/obstacles are identified.

The road condition recognition method of the present invention is based on the existing common lower limb accessories, and installs a heel sensor module on the heel of the foot tissue (the person with a disabled lower limb is the lower limb auxiliary device prosthetic foot 81, and the person with a healthy lower limb is the wearer's foot 82) 1. Install the toe sensor module on the toe of the foot tissue. 2. Install the gyroscope module 3 on the calf tissue (the lower limb accessory calf 71 for the incomplete lower limbs, and the wearer’s calf 72 for the healthy lower limbs), and use the control module 4 for processing The information of each sensor, according to the information extracted by the sensor, is comprehensively analyzed to realize the effective identification of different road conditions during the movement of the lower limbs of the human body. According to different road conditions, the driving module 5 is used to control the lower limb assistive device to make corresponding actions, so that the lower limb assistive device and the wearer can truly reach the same pace, so that it can easily complete daily activities such as climbing stairs, climbing slopes, and crossing obstacles.

What is not mentioned in the present invention is applicable to the prior art.

Claims (1)

1. A road condition recognition method for lower extremity walking motion, characterized in that the recognition aid hardware structure of the road condition recognition method is: heel sensor module, tiptoe sensor module, gyroscope module, control module, drive module, prosthetic knee joint , Lower limb assistive calf and lower limb assistive prosthetic foot; The road condition recognition method includes the following steps: 1). Selection of special points of angular velocity signal The signal collected by the gyroscope module is input to the control module, and after being processed by the control module, the angular velocity signal of the lower limb swinging back and forth during the calf movement process is obtained; the gyroscope module detects and obtains a signal of a gait cycle, and determines a step The three special points of the angular velocity signal in the state cycle are used as the basis for the heel sensor module and the toe sensor module to distinguish the road conditions. The three special points are: the starting point of the periodic signal, the minimum of the transition from the first waveform to the second waveform of the periodic signal value point, the peak point of the second peak of the periodic signal; 2). Specific identification process of six road conditions (1) When the signal detected by the gyroscope module is at the starting point, judge whether the toe sensor module detects a foreign object or occlusion; if the toe sensor module detects a foreign object or occlusion, it is an obstacle/uphill/stairs three road conditions , denoted as mode 1, the control module regulates the drive module to control the lower limbs assisting calf to raise the leg; if the toe sensor module does not detect foreign objects or occlusions, there are three road conditions: flat ground/downhill/down stairs, denoted as mode 2; (2) When the gyroscope module detects that the signal reaches the minimum value point, the three road conditions of mode 1 are judged: if the heel sensor module detects that there is a foreign object or occlusion behind the prosthetic foot of the lower limb auxiliary device, the road condition is an obstacle; If the heel sensor module does not detect any foreign objects or occlusions behind the prosthetic foot of the lower limb assistive device, it is the two road conditions of going up stairs/uphill, which is recorded as mode 3; at the same time, the three road conditions of mode 2 are judged, if the heel sensor module If no foreign object or occlusion is detected, the road condition is flat; if the heel sensor module detects a foreign object or occlusion, it is two road conditions: down stairs/downhill, recorded as mode 4; (3) When the signal measured by the gyroscope module reaches the peak point, use the toe sensor module to distinguish the two road conditions of mode 3: if the toe sensor module detects foreign objects or obstructions, the road condition is going up stairs; if the toe sensor module If there is no foreign object or occlusion detected, the road condition is uphill; at the same time, the toe sensor module is used to distinguish the two road conditions of mode 4: if the toe sensor module detects a foreign object or occlusion, the road condition is down stairs; if the toe sensor module does not If a foreign object or obstruction is detected, the road condition is downhill.