CN104224124B

CN104224124B - Outside recognition methods and equipment in limbs

Info

Publication number: CN104224124B
Application number: CN201410468705.6A
Authority: CN
Inventors: 刘浩
Original assignee: Beijing Zhigu Tech Co Ltd
Current assignee: Beijing Zhigu Tech Co Ltd
Priority date: 2014-09-15
Filing date: 2014-09-15
Publication date: 2016-10-05
Anticipated expiration: 2034-09-15
Also published as: CN104224124A

Abstract

This application provides outside recognition methods and equipment in a kind of limbs, relate to Wearable device field.Described method includes one first humidity information obtaining the first side of limbs of user, and described first side is inner side or the outside of described limbs；According to described first humidity information and a reference information, identify that whether described first side is the inner side of described limbs.The equipment that described method and apparatus, beneficially user are worn is arranged automatically according to recognition result, promotes Consumer's Experience.

Description

Outside recognition methods and equipment in limbs

Technical field

The application relates to Wearable device field, particularly relates to outside recognition methods and equipment in a kind of limbs.

Background technology

In recent years, along with the development of Wearable device, Intelligent spire lamella, Intelligent bracelet, intelligent glasses etc. progress into the life of people, enrich and facilitate the life of people greatly.

On intelligent watch, the body-sensing sensor of configuration, can be continuously monitored the body-sensing data of user such as body temperature, heart rate and blood glucose etc., to provide a user with health care service.This body-sensing sensor or be embedded in the back side of dial plate, it is embedded in the inner face of watchband, according to measuring principle, this type of body-sensing sensor must be close to the inner face of user's wrist just can accurately measure the body-sensing data of user, this has resulted in user must wear intelligent watch in a fixed manner, brings inconvenience to user.Such as, if body-sensing sensor is embedded in the inner face of watchband, then user must be worn on the dial plate of intelligent watch the outside of wrist, and this makes troubles to the user getting used to being worn on dial plate wrist inner face.

Summary of the invention

The purpose of the application is: provide outside recognition methods and equipment in a kind of limbs.

An aspect according at least one embodiment of the application, it is provided that outside recognition methods in a kind of limbs, described method includes:

Obtaining one first humidity information of the first side of limbs of user, described first side is inner side or the outside of described limbs；

According to described first humidity information and a reference information, identify that whether described first side is the inner side of described limbs.

Another aspect according at least one embodiment of the application, it is provided that in a kind of limbs, outside identifies equipment, and described equipment includes:

One first acquisition module, for obtaining one first humidity information of the first side of limbs of user, described first side is inner side or the outside of described limbs；

One identification module, for according to described first humidity information and a reference information, identifies that whether described first side is the inner side of described limbs.

Another aspect according at least one embodiment of the application, it is provided that outside recognition methods in a kind of limbs, described method includes:

Obtaining one first body-sensing information of the first side of limbs of user, described first side is inner side or the outside of described limbs；

According to described first body-sensing information and a reference information, identify that whether described first side is the inner side of described limbs.

One first acquisition module, for obtaining one first body-sensing information of the first side of limbs of user, described first side is inner side or the outside of described limbs；

One identification module, for according to described first body-sensing information and a reference information, identifies that whether described first side is the inner side of described limbs.

Outside recognition methods and equipment in limbs described in the embodiment of the present application, obtain the first humidity information of the first side of limbs of user, and then be whether the inner side of described limbs according to the first side described in described first humidity information and a reference information identification, thus provide outside recognition methods in a kind of limbs, the Wearable device being conducive to user is arranged automatically according to recognition result, promotes Consumer's Experience.

Accompanying drawing explanation

Fig. 1 is the flow chart of the interior outside recognition methods of limbs described in one embodiment of the application；

Fig. 2 be in one embodiment of the application inside wrist and palm inside schematic diagram；

Fig. 3 is the contrast schematic diagram of the skin conductance information in the interior outside of wrist in one embodiment of the application；

Fig. 4 is the refinement flow chart of step S140a described in one embodiment of the application；

Fig. 5 is the refinement flow chart of step S140a described in another embodiment of the application；

Fig. 6 is the contrast schematic diagram of the temperature information in the interior outside of wrist in one embodiment of the application；

Fig. 7 is the refinement flow chart of step S140b described in one embodiment of the application；

Fig. 8 is the refinement flow chart of step S140b described in another embodiment of the application；

Fig. 9 is the contrast schematic diagram of the acid-base value information in the interior outside of wrist in one embodiment of the application；

Figure 10 is the refinement flow chart of step S140c described in one embodiment of the application；

Figure 11 is the refinement flow chart of step S140c described in another embodiment of the application；

Figure 12 is the contrast schematic diagram of the PPG information in the interior outside of wrist in one embodiment of the application；

Figure 13 is the refinement flow chart of step S140d described in one embodiment of the application；

Figure 14 is the refinement flow chart of step S140d described in another embodiment of the application；

Figure 15 is the contrast schematic diagram of the humidity information in the interior outside of wrist in one embodiment of the application；

Figure 16 is the refinement flow chart of step S140e described in one embodiment of the application；

Figure 17 is the refinement flow chart of step S140e described in another embodiment of the application；

Figure 18 is the contrast schematic diagram of the blood oxygenation information in the interior outside of wrist in one embodiment of the application；

Figure 19 is the refinement flow chart of step S140f described in one embodiment of the application；

Figure 20 is the refinement flow chart of step S140f described in another embodiment of the application；

Figure 21 is the contrast schematic diagram of the fatty information in the interior outside of wrist in one embodiment of the application；

Figure 22 is the refinement flow chart of step S140g described in one embodiment of the application；

Figure 23 is the refinement flow chart of step S140g described in another embodiment of the application；

Figure 24 is the flow chart of the interior outside recognition methods of limbs in one embodiment of the application；

Figure 25 is the function structure chart that the interior outside of limbs described in one embodiment of the application identifies equipment；

Figure 26 is the function structure chart that the interior outside of limbs described in one embodiment of the application identifies equipment；

Figure 27 is the function structure chart that the interior outside of limbs described in another embodiment of the application identifies equipment；

Figure 28 is the function structure chart that the interior outside of limbs described in another embodiment of the application identifies equipment；

Figure 29 is the function structure chart that the interior outside of limbs described in another embodiment of the application identifies equipment；

Figure 30 is the function structure chart that the interior outside of limbs described in another embodiment of the application identifies equipment；

Figure 31 is the function structure chart that the interior outside of limbs described in another embodiment of the application identifies equipment；

Figure 32 is the function structure chart that the interior outside of limbs described in another embodiment of the application identifies equipment；

Figure 33 is the function structure chart that the interior outside of limbs described in another embodiment of the application identifies equipment；

Figure 34 is the function structure chart that the interior outside of limbs described in another embodiment of the application identifies equipment；

Figure 35 is the function structure chart that the interior outside of limbs described in another embodiment of the application identifies equipment；

Figure 36 is the function structure chart that the interior outside of limbs described in another embodiment of the application identifies equipment；

Figure 37 is the function structure chart that the interior outside of limbs described in another embodiment of the application identifies equipment；

Figure 38 is the function structure chart that the interior outside of limbs described in another embodiment of the application identifies equipment；

Figure 39 is the function structure chart that the interior outside of limbs described in another embodiment of the application identifies equipment；

Figure 40 is the function structure chart that the interior outside of limbs described in another embodiment of the application identifies equipment；

Figure 41 is the hardware architecture diagram that the interior outside of limbs described in one embodiment of the application identifies equipment.

Detailed description of the invention

Below in conjunction with the accompanying drawings and embodiment, the detailed description of the invention of the application is described in further detail.Following example are used for illustrating the application, but are not limited to scope of the present application.

Skilled artisan understands that, in embodiments herein, the size of the sequence number of following each step is not meant to the priority of execution sequence, and the execution sequence of each step should determine with its function and internal logic, and the implementation process of the embodiment of the present application should not constituted any restriction.

Fig. 1 is the flow chart of the interior outside recognition methods of limbs described in one embodiment of the application, and described method can realize on the identification equipment of outside in such as one limbs.As it is shown in figure 1, described method includes:

S120: obtaining one first body-sensing information of the first side of limbs of user, described first side is inner side or the outside of described limbs；

S140: according to described first body-sensing information and a reference information, identifies that whether described first side is the inner side of described limbs.

Method described in the embodiment of the present application, obtain the first body-sensing information of the first side of limbs of user, and then be whether the inner side of described limbs according to the first side described in described first body-sensing information and a reference information identification, thus provide outside recognition methods in a kind of limbs, the Wearable device being conducive to user is arranged automatically according to recognition result, promotes Consumer's Experience.

Below with reference to detailed description of the invention, describe the function of described step S120 and S140 in detail.

S120: obtaining one first body-sensing information of the first side of limbs of user, described first side is inner side or the outside of described limbs.

Wherein, described limbs can include the upper limb of described user, lower limb.Concrete, the inner side of described limbs can be the inner side of wrist, the inner side of palm, the inner side of sole, and the outside of corresponding described limbs can be with the outside of wrist, the outside of palm, the outside of sole.As in figure 2 it is shown, the region that in the inner side of described palm i.e. Fig. 2, the palm of the hand 220 is corresponding in the palm of the hand 220 side with finger, the region that the outside of palm i.e. the back of the hand is corresponding in the back of the hand side with finger；In the inner side of described wrist i.e. Fig. 2 and the described palm of the hand 220 homonymy the first area between palm and forearm 210, the outside of wrist is relative with described first area 210, namely and described the back of the hand homonymy the second area between palm and forearm.The inner side of described sole is the region that sole is corresponding, and the outside of described sole is the region that instep is corresponding.

Described first side is inner side or the outside of described wrist, or the inner side of described palm or outside, or the outside of described sole or inner side.For the sake of Jian Dan, many below is to illustrate as a example by the inner side of described wrist or outside by described first side.

Described first body-sensing information can be the skin conductance information of described limbs the first side, body temperature information, acid-base value information, PPG information, humidity information, blood oxygenation information, fat information etc., it can be obtained by the corresponding body-sensing sensor contacted to user's skin, current Intelligent spire lamella, intelligent watch etc. the most all have these sensors, therefore, the enforcement of described method will not increase the hardware cost of existing Wearable.

A) described first body-sensing information can be the skin conductance information of described first side, the i.e. first skin conductance information.Described step S140 is:

S140a: according to described first skin conductance information and a reference information, identifies that whether described first side is the inner side of described limbs.

Inventor finds under study for action, owing to the sweat gland quantity inside limbs is more than outside limbs, skin outside limbs is more coarse than inside limbs simultaneously, and the skin conductance inside the limbs of user and the skin conductance outside limbs have marked difference statistically, and i.e. both variances are less than or equal to 0.05.As shown in Figure 3, upper curve represents that the skin conductivity signal inside the wrist to a user is sampled the curve of the skin conductance information obtained, and lower curve represents that the extracarpal skin conductivity signal of the hands to described user is sampled and obtains the curve of skin conductance information.Wherein, horizontal axis representing time, unit is the second, and the longitudinal axis represents conductance, and unit is micro-west.It will be seen that two curves have significant difference, can obtain after analysis, the meansigma methods of the skin conductance information inside wrist is significantly greater than the meansigma methods of the extracarpal skin conductance information of hands.It is similar to, inventor also finds that the meansigma methods of the skin conductance information inside palm is significantly greater than the meansigma methods of the skin conductance information outside palm, and the meansigma methods of the skin conductance information inside sole is significantly greater than the meansigma methods of the skin conductance information outside sole.Therefore, can realize the identification in outside in limbs based on the herein described method of this principle.

In one embodiment, the Second Skin conduction information that the second side that described reference information is relative with described first side on described limbs obtains.Such as, body-sensing sensor described in two groups can be set, gather corresponding skin conductance information simultaneously in the first side of described limbs and the second side, and using the skin conductance information in the second side collection as described reference information.

In present embodiment, by the meansigma methods of relatively described first skin conductance information and the size of the meansigma methods of described Second Skin conduction information, described step S140a can identify that whether described first side is the inner side of described limbs, concrete, as shown in Figure 4, it may include that

S141a: in response to described first skin conductance information meansigma methods more than described Second Skin conduction information meansigma methods, identify that described first side is the inner side of described limbs；

S142a: in response to described first skin conductance information meansigma methods less than described Second Skin conduction information meansigma methods, identify that described first side is not the inner side of described limbs.

In another embodiment, described reference information can be the inside skin conduction information according to described limbs and the lateral cutaneous conduction threshold value that determines of information.Concrete, as it is shown in figure 5, described step S140a may include that

S141a ': the meansigma methods in response to described first skin conductance information is more than described threshold value, identifies that described first side is the inner side of described limbs；

S142a ': the meansigma methods in response to described first skin conductance information is less than described threshold value, identifies that described first side is not the inner side of described limbs.

Such as, gather the inside skin conduction information of described limbs and the lateral cutaneous conduction information of described limbs in advance, and analyze and process, it is assumed that the meansigma methods of described inside skin conduction information falls into the first interval (I_min,I_max), it is assumed that the meansigma methods of described lateral cutaneous conduction information falls into the second interval (O_min,O_max), then have O_max＜ I_min, then may determine that described threshold value is M, and O_max＜ M ＜ I_min.It is to say, described threshold value M is a numerical value between described first interval and described second interval.

Therefore, if the meansigma methods of described first skin conductance information is more than described threshold value M, then it is assumed that it falls into described first interval, and described first side is the inner side of described limbs；If the meansigma methods of described first skin conductance information is less than described threshold value M, then it is assumed that it falls into described second interval, and described first side is not the inner side of described limbs, is i.e. the outside of described limbs.

B) described first body-sensing information can be the body temperature information of described first side, the i.e. first body temperature information.Described step S140 is:

S140b: according to described first body temperature information and a reference information, identifies that whether described first side is the inner side of described limbs.

Inventor finds under study for action, and owing to comparing closer to arteries outside limbs inside limbs, the body temperature inside the limbs of user can be higher than the body temperature outside limbs.As shown in Figure 6, first curve 610 represents and uses the first body temperature trans to sample the temperature signals inside the wrist of a user curve of the body temperature information obtained, and the second curve 620 represents that using the second body temperature trans to sample the extracarpal temperature signals of hands of described user obtains the curve of body temperature information.Wherein, horizontal axis representing time, unit is the second, and the longitudinal axis represents temperature, and unit is degree Celsius, and 0 moment, corresponding described user started to wear described first body temperature trans and the time of described second body temperature trans.

It will be seen that two curves are at t in Fig. 6₁Having significant difference before moment, can obtain after analysis, the body temperature inside wrist is significantly greater than the extracarpal body temperature of hands.At t₁After moment, two curves gradually merge, and this is that the body temperature making two sensors detect due to the conductive force of described first body temperature trans of connection and the connecting portion of described second body temperature trans tends to identical.In another is tested, we eliminate the connecting portion in the middle of two body temperature transes, and the body temperature inside the temperature curve finally given display wrist is always more than hands extracarpal body temperature value, and its temperature difference is about 0.2 DEG C.

Being similar to, inventor also finds that the body temperature inside palm is significantly greater than the body temperature outside palm, and the body temperature inside sole is significantly greater than the body temperature outside sole.Therefore, can realize the identification in outside in limbs based on the herein described method of this principle.

In one embodiment, one second body temperature information that the second side that described reference information is relative with described first side on described limbs obtains.Such as, body-sensing sensor described in two groups can be set, gather corresponding body temperature information simultaneously in the first side of described limbs and the second side, and using the body temperature information in the second side collection as described reference information.

In present embodiment, by the meansigma methods of relatively described first body temperature information and the size of the meansigma methods of described second body temperature information, described step S140b can identify that whether described first side is the inner side of described limbs.The meansigma methods of described first body temperature information is the meansigma methods of the temperature value that multiple sampled points are corresponding in described first body temperature information, similar, and the meansigma methods of described second body temperature information is the meansigma methods of the temperature value that multiple sampled points are corresponding in described second body temperature information.By using meansigma methods, single sampled point can be avoided to cause identifying mistake in the case of sampling error occurs, improve recognition accuracy.Concrete, seeing Fig. 7, described step S140b may include that

S141b: in response to the meansigma methods of described first body temperature information more than the meansigma methods of described second body temperature information, identify that described first side is the inner side of described limbs；

S142b: in response to the meansigma methods of described first body temperature information less than the meansigma methods of described second body temperature information, identify that described first side is not the inner side of described limbs.

In another embodiment, the threshold value that described reference information can be the inner side body temperature information according to described limbs and outside body temperature information determines.Concrete, seeing Fig. 8, described step S140b may include that

S141b ': the meansigma methods in response to described first body temperature information is more than described threshold value, identifies that described first side is the inner side of described limbs；

S142b ': the meansigma methods in response to described first body temperature information is less than described threshold value, identifies that described first side is not the inner side of described limbs.

Such as, gather the inner side body temperature information of described limbs and the outside body temperature information of described limbs in advance, and analyze and process, it is assumed that the meansigma methods of described inner side body temperature information falls into the first interval (I_min,I_max), it is assumed that the meansigma methods of described outside body temperature information falls into the second interval (O_min,O_max), then have O_max＜ I_min, then may determine that described threshold value is M, and O_max＜ M ＜ I_min.It is to say, described threshold value M is a numerical value between described first interval and described second interval.

Therefore, if the meansigma methods of described first body temperature information is more than described threshold value M, then it is assumed that it falls into described first interval, and described first side is the inner side of described limbs；If the meansigma methods of described first body temperature information is less than described threshold value M, then it is assumed that it falls into described second interval, and described first side is not the inner side of described limbs, is i.e. the outside of described limbs.

It should be noted that, if outside identifies that equipment contacts the inner side and outer side of described limbs in described limbs simultaneously, and there is the conduction of heat by described equipment, the acquisition time of the most described first body temperature information and described second body temperature information should complete within the scheduled time from wearing described equipment, i.e. should be at t described in Fig. 6₁Completed before moment, cause to avoid two strips temperature curve to merge identifying mistake.

C) described first body-sensing information can be the acid-base value information of described first side, the i.e. first acid-base value information.Described step S140 is:

S140c: according to described first acid-base value information and a reference information, identifies that whether described first side is the inner side of described limbs.

Inventor finds under study for action, owing to the sweat gland quantity inside limbs is more than outside limbs, and, the acid-base value (i.e. pH value) inside the limbs of user is significantly less than the acid-base value outside limbs.As shown in Figure 9, first curve 910 represents that the extracarpal acid-base value signal of the hands to a user is sampled the curve of the acid-base value information obtained, and the second curve 920 represents that the acid-base value signal inside the wrist to described user is sampled and obtains the curve of acid-base value information.Wherein, horizontal axis representing time, unit is the second, and the longitudinal axis represents acid-base value.

It will be seen that two curves are at t in Fig. 9₂Having significant difference before moment, can obtain after analysis, the extracarpal acid-base value of hands is significantly greater than the acid-base value inside wrist.At t₂After moment, two curves gradually merge, and this is truly to use environment due to this experimental simulation user, wear after outside in described limbs identifies equipment a period of time, described limbs have perspiration to ooze out.In another is tested, we eliminate the impact (as tested in cold environment) that perspiration oozes out, and the acid-base value curve the finally given display extracarpal acid-base value of hands is always more than the pH value inside wrist, and its difference is about 0.3～0.4.

Being similar to, inventor also finds that the acid-base value outside palm is significantly greater than the acid-base value inside palm, and the acid-base value outside sole is significantly greater than the acid-base value inside sole.Therefore, can realize the identification in outside in limbs based on the herein described method of this principle.

In one embodiment, the one second acid-base value information that the second side that described reference information is relative with described first side on described limbs obtains.Such as, body-sensing sensor described in two groups can be set, gather corresponding acid-base value information simultaneously in the first side of described limbs and the second side, and using the acid-base value information in the second side collection as described reference information.

In present embodiment, by the meansigma methods of relatively described first acid-base value information and the size of the meansigma methods of described second acid-base value information, described step S140c can identify that whether described first side is the inner side of described limbs.The meansigma methods of described first acid-base value information is the meansigma methods of the pH value that multiple sampled points are corresponding in described first acid-base value information, being similar to, the meansigma methods of described second acid-base value information is the meansigma methods of the pH value that multiple sampled points are corresponding in described second acid-base value information.By using meansigma methods, single sampled point can be avoided to cause identifying mistake in the case of sampling error occurs, improve recognition accuracy.Concrete, seeing Figure 10, described step S140c may include that

S141c: in response to the meansigma methods of described first acid-base value information less than the meansigma methods of described second acid-base value information, identify that described first side is the inner side of described limbs；

S142c: in response to the meansigma methods of described first acid-base value information more than the meansigma methods of described second acid-base value information, identify that described first side is not the inner side of described limbs.

In another embodiment, the threshold value that described reference information can be the inner side acid-base value information according to described limbs and outside acid-base value information determines.Concrete, seeing Figure 11, described step S140c may include that

S141c ': the meansigma methods in response to described first acid-base value information is less than described threshold value, identifies that described first side is the inner side of described limbs；

S142c ': the meansigma methods in response to described first acid-base value information is more than described threshold value, identifies that described first side is not the inner side of described limbs.

Such as, gather the inner side acid-base value information of described limbs and the outside acid-base value information of described limbs in advance, and analyze and process, it is assumed that the meansigma methods of described inner side acid-base value information falls into the first interval (I_min,I_max), it is assumed that the meansigma methods of described outside acid-base value information falls into the second interval (O_min,O_max), then have I_max＜ O_min, then may determine that described threshold value is M, and I_max＜ M ＜ O_min.It is to say, described threshold value M is a numerical value between described first interval and described second interval.

Therefore, if the meansigma methods of described first acid-base value information is more than described threshold value M, then it is assumed that it falls into described second interval, and described first side is the outside of described limbs；If the meansigma methods of described first acid-base value information is less than described threshold value M, then it is assumed that it falls into described first interval, and described first side is not the outside of described limbs, is i.e. the inner side of described limbs.

It should be noted that, if outside identifies that equipment contacts the inner side and outer side of described limbs in described limbs, and there is the situation that contact portion has perspiration to ooze out, the acquisition time of the most described first acid-base value information and described second acid-base value information should complete within the scheduled time from wearing described equipment, i.e. should be at t described in Fig. 9₂Completed before moment, i.e. completed before perspiration oozes out, cause to avoid two acid-base value curves to merge identifying mistake.

D) described first body-sensing information can be the PPG information of described first side, the i.e. the oneth PPG information.A described PPG information can use reflection mode or transmission mode to obtain.When using reflection mode, the first side that corresponding PPG sensor can be arranged on described limbs obtains；When using transmission mode, the detection signal that the transmitting terminal of corresponding PPG sensor sends receives through the first receiving end, rear flank of described limbs, and described detection signal is without second side relative with described first side.

Described step S140 is:

S140d: according to a described PPG information and a reference information, identifies that whether described first side is the inner side of described limbs.

Inventor finds under study for action, higher owing to comparing limbs lateral cutaneous light transmittance inside limbs, and the averaged amplitude value of the PPG information inside the limbs of user can be higher than the averaged amplitude value of the PPG information outside limbs.As shown in figure 12, first curve 1210 represents and uses a PPG sensor to sample the PPG signal inside the wrist of a user curve of the PPG information obtained, and the second curve 1220 represents that using the 2nd PPG sensor to sample the hands extracarpal PPG signal of described user obtains the curve of PPG information.Wherein, horizontal axis representing time, unit is the second, and the longitudinal axis represents voltage amplitude value, and unit is volt.It will be seen that two curves have significant difference in Figure 12, can obtain after analysis, the averaged amplitude value of the PPG information inside wrist can be higher than the averaged amplitude value of hands extracarpal PPG information.Wherein, the averaged amplitude value of described PPG information is the meansigma methods of multiple PPG range value.

Being similar to, inventor also finds that the averaged amplitude value of the PPG information inside palm is significantly greater than the averaged amplitude value of the PPG information outside palm, and the averaged amplitude value of the PPG information inside sole is significantly greater than the averaged amplitude value of the PPG information outside sole.Therefore, can realize the identification in outside in limbs based on the herein described method of this principle.

In one embodiment, one the 2nd PPG information that the second side that described reference information is relative with described first side on described limbs obtains.Such as, body-sensing sensor described in two groups can be set, gather corresponding PPG information simultaneously in the first side of described limbs and the second side, and using the PPG information in the second side collection as described reference information.

In present embodiment, by the averaged amplitude value of a relatively described PPG information and the size of the averaged amplitude value of described 2nd PPG information, described step S140b can identify that whether described first side is the inner side of described limbs.The averaged amplitude value of a described PPG information is the meansigma methods of the PPG range value that multiple sampled points are corresponding in a described PPG information, being similar to, the averaged amplitude value of described 2nd PPG information is the meansigma methods of the PPG range value that multiple sampled points are corresponding in described 2nd PPG information.By using meansigma methods, single sampled point can be avoided to cause identifying mistake in the case of sampling error occurs, improve recognition accuracy.Concrete, seeing Figure 13, described step S140d may include that

S141d: in response to the averaged amplitude value of a described PPG information more than the averaged amplitude value of described 2nd PPG information, identify that described first side is the inner side of described limbs；

S142d: in response to the averaged amplitude value of a described PPG information less than the averaged amplitude value of described 2nd PPG information, identify that described first side is not the inner side of described limbs.

In another embodiment, the threshold value that described reference information can be the inner side PPG information according to described limbs and outside P PG information determines.Concrete, seeing Figure 14, described step S140d may include that

S141d ': the averaged amplitude value in response to a described PPG information is more than described threshold value, identifies that described first side is the inner side of described limbs；

S142d ': the averaged amplitude value in response to a described PPG information is less than described threshold value, identifies that described first side is not the inner side of described limbs.

Such as, gather inner side PPG information and the outside P PG information of described limbs of described limbs in advance, and analyze and process, it is assumed that the averaged amplitude value of described inner side PPG information falls into the first interval (I_min,I_max), it is assumed that the averaged amplitude value of described outside P PG information falls into the second interval (O_min,O_max), then have O_max＜ I_min, then may determine that described threshold value is M, and O_max＜ M ＜ I_min.It is to say, described threshold value M is a numerical value between described first interval and described second interval.

Therefore, if the averaged amplitude value of a described PPG information is more than described threshold value M, then it is assumed that it falls into described first interval, and described first side is the inner side of described limbs；If the averaged amplitude value of a described PPG information is less than described threshold value M, then it is assumed that it falls into described second interval, and described first side is not the inner side of described limbs, is i.e. the outside of described limbs.

E) described first body-sensing information can be the humidity information of described first side, the i.e. first humidity information.Described step S140 is:

S140e: according to described first humidity information and a reference information, identifies that whether described first side is the inner side of described limbs.

Inventor finds under study for action, has more sweat gland owing to comparing inside limbs outside limbs, and the humidity inside the limbs of user can be higher than the humidity outside limbs.As shown in figure 15, first curve 1510 represents and uses the first humidity sensor to sample the moisture signal inside the wrist of a user curve of the humidity information obtained, and the second curve 1520 represents that using the second humidity sensor to sample the extracarpal moisture signal of hands of described user obtains the curve of humidity information.Wherein, horizontal axis representing time, unit is the second, and the longitudinal axis represents humidity.It will be seen that two curves show in Figure 15, the humidity inside wrist is significantly greater than the extracarpal humidity of hands.

Being similar to, inventor also finds that the humidity inside palm is significantly greater than the humidity outside palm, and the humidity inside sole is significantly greater than the humidity outside sole.Therefore, can realize the identification in outside in limbs based on the herein described method of this principle.

In one embodiment, one second humidity information that the second side that described reference information is relative with described first side on described limbs obtains.Such as, body-sensing sensor described in two groups can be set, gather corresponding humidity information simultaneously in the first side of described limbs and the second side, and using the humidity information in the second side collection as described reference information.

In present embodiment, by the meansigma methods of relatively described first humidity information and the size of the meansigma methods of described second humidity information, described step S140e can identify that whether described first side is the inner side of described limbs.The meansigma methods of described first humidity information is the meansigma methods of the humidity value that multiple sampled points are corresponding in described first humidity information, similar, and the meansigma methods of described second humidity information is the meansigma methods of the humidity value that multiple sampled points are corresponding in described second humidity information.By using meansigma methods, single sampled point can be avoided to cause identifying mistake in the case of sampling error occurs, improve recognition accuracy.Concrete, seeing Figure 16, described step S140e may include that

S141e: in response to the meansigma methods of described first humidity information more than the meansigma methods of described second humidity information, identify that described first side is the inner side of described limbs；

S142e: in response to the meansigma methods of described first humidity information less than the meansigma methods of described second humidity information, identify that described first side is not the inner side of described limbs.

In another embodiment, the threshold value that described reference information can be the inner side humidity information according to described limbs and outside humidity information determines.Concrete, seeing Figure 17, described step S140e may include that

S141e ': the meansigma methods in response to described first humidity information is more than described threshold value, identifies that described first side is the inner side of described limbs；

S142e ': the meansigma methods in response to described first humidity information is less than described threshold value, identifies that described first side is not the inner side of described limbs.

Such as, gather the inner side humidity information of described limbs and the outside humidity information of described limbs in advance, and analyze and process, it is assumed that the meansigma methods of described inner side humidity information falls into the first interval (I_min,I_max), it is assumed that the meansigma methods of described outside humidity information falls into the second interval (O_min,O_max), then have O_max＜ I_min, then may determine that described threshold value is M, and O_max＜ M ＜ I_min.It is to say, described threshold value M is a numerical value between described first interval and described second interval.

Therefore, if the meansigma methods of described first humidity information is more than described threshold value M, then it is assumed that it falls into described first interval, and described first side is the inner side of described limbs；If the meansigma methods of described first humidity information is less than described threshold value M, then it is assumed that it falls into described second interval, and described first side is not the inner side of described limbs, is i.e. the outside of described limbs.

F) described first body-sensing information can be the blood oxygenation information of described first side, the i.e. first blood oxygenation information.Described blood oxygenation information can be blood oxygen saturation, and it can use reflection mode or transmission mode to obtain.Such as, when using reflection mode to obtain described first blood oxygenation information, the first side that corresponding blood oxygen transducer can be arranged on described limbs obtains；When using transmission mode to obtain described first blood oxygenation information, the detection signal that the transmitting terminal of corresponding blood oxygen transducer sends receives through the first receiving end, rear flank of described limbs, and described detection signal is without second side relative with described first side.

Described step S140 is:

S140f: according to described first blood oxygenation information and a reference information, identifies that whether described first side is the inner side of described limbs.

Inventor finds under study for action, and blood oxygen saturation is usually and measures the absorbtivity of the light of different wave length according to blood in blood vessel.Owing to the vein blood vessel inside limbs is significantly more than limbs lateral vein blood vessel, arteries distribution simultaneously is deeper, it is normally at the middle part between limbs inner side and outer side, therefore, the meansigma methods of the blood oxygenation information recorded inside the limbs of user can be higher than the meansigma methods of the blood oxygenation information recorded outside limbs.As shown in figure 18, first curve 1810 represents and uses the first blood oxygen transducer to sample the blood oxygen signal inside the wrist of a user curve of the blood oxygenation information obtained, and the second curve 1820 represents that using the second blood oxygen transducer to sample the hands extracarpal blood oxygen signal of described user obtains the curve of blood oxygenation information.Wherein, horizontal axis representing time, unit is the second, and the longitudinal axis represents blood oxygen saturation.It will be seen that two curves have significant difference in Figure 18, can obtain after analysis, the meansigma methods of the blood oxygenation information inside wrist can be higher than the meansigma methods of the extracarpal blood oxygenation information of hands.Wherein, the meansigma methods of described blood oxygenation information is the meansigma methods of the blood oxygen saturation that multiple sampled point is corresponding.

Being similar to, inventor also finds that the meansigma methods of the blood oxygenation information inside palm is significantly greater than the meansigma methods of the blood oxygenation information outside palm, and the meansigma methods of the blood oxygenation information inside sole is significantly greater than the meansigma methods of the blood oxygenation information outside sole.Therefore, can realize the identification in outside in limbs based on the herein described method of this principle.

In one embodiment, one second blood oxygenation information that the second side that described reference information is relative with described first side on described limbs obtains.Such as, body-sensing sensor described in two groups can be set, gather corresponding blood oxygenation information simultaneously in the first side of described limbs and the second side, and using the blood oxygenation information in the second side collection as described reference information.

In present embodiment, by the meansigma methods of relatively described first blood oxygenation information and the size of the meansigma methods of described second blood oxygenation information, described step S140f can identify that whether described first side is the inner side of described limbs.The meansigma methods of described first blood oxygenation information is the meansigma methods of the blood oxygen saturation that multiple sampled points are corresponding in described first blood oxygenation information, being similar to, the meansigma methods of described second blood oxygenation information is the meansigma methods of the blood oxygen saturation that multiple sampled points are corresponding in described second blood oxygenation information.By using meansigma methods, single sampled point can be avoided to cause identifying mistake in the case of sampling error occurs, improve recognition accuracy.Concrete, seeing Figure 19, described step S140f may include that

S141f: in response to the meansigma methods of described first blood oxygenation information more than the meansigma methods of described second blood oxygenation information, identify that described first side is the inner side of described limbs；

S142f: in response to the meansigma methods of described first blood oxygenation information less than the meansigma methods of described second blood oxygenation information, identify that described first side is not the inner side of described limbs.

In another embodiment, the threshold value that described reference information can be the inner side blood oxygenation information according to described limbs and outside blood oxygenation information determines.Concrete, seeing Figure 20, described step S140f may include that

S141f ': the meansigma methods in response to described first blood oxygenation information is more than described threshold value, identifies that described first side is the inner side of described limbs；

S142f ': the meansigma methods in response to described first blood oxygenation information is less than described threshold value, identifies that described first side is not the inner side of described limbs.

Such as, gather the inner side blood oxygenation information of described limbs and the outside blood oxygenation information of described limbs in advance, and analyze and process, it is assumed that the meansigma methods of described inner side blood oxygenation information falls into the first interval (I_min,I_max), it is assumed that the meansigma methods of described outside blood oxygenation information falls into the second interval (O_min,O_max), then have O_max＜ I_min, then may determine that described threshold value is M, and O_max＜ M ＜ I_min.It is to say, described threshold value M is a numerical value between described first interval and described second interval.

Therefore, if the meansigma methods of described first blood oxygenation information is more than described threshold value M, then it is assumed that it falls into described first interval, and described first side is the inner side of described limbs；If the meansigma methods of described first blood oxygenation information is less than described threshold value M, then it is assumed that it falls into described second interval, and described first side is not the inner side of described limbs, is i.e. the outside of described limbs.

G) described first body-sensing information can be the fatty information of described first side, the i.e. first fat information.Described fat information can be fat percentage, and such as, described first fat information can be that corresponding fats measurement sensor measures, in the first side of described limbs, the fat percentage obtained.

Described step S140 is:

S140g: according to a described first fat information and reference information, identifies that whether described first side is the inner side of described limbs.

Inventor finds in research process, and the method for the current main flow of the content of body fat, i.e. fat percentage is first to measure bulk resistor, then speculates the content of fat according to bulk resistor.The health water content of people is about 70%, and these moisture content overwhelming majority are present in blood, lean meat and internal organs, and in fat, water content is extremely low.Internal moisture content presents low resistance owing to being dissolved with various composition, and fat but presents high resistance, thus in human body, the scale effect of fat and water is to the resistance of human body, if it is considered that fat and the combined resistance of moisture content, then fat more many human body resistances value is the highest.And the limbs of people, such as wrist, due to the result of natural evolution, the fat content in outside is higher than inner side.For wrist, outside wrist, that muscle and arteries could be protected to be difficult to is injured for fat content height；Meanwhile, outside the moisture wrist to be significantly higher than inside wrist, this be due to wrist inside sweat gland quantity wrist to be significantly higher than outside.So comprehensive the two factor, the inner side of the extracarpal fat percentage of hands wrist to be significantly higher than.As shown in figure 21, first curve 2110 represents and uses the first fats measurement sensor to sample the fat content inside the wrist of a user curve of the fatty information obtained, and the second curve 2120 represents that using the second fat sensor to sample the extracarpal fat content of hands of described user obtains the curve of fat information.Wherein, horizontal axis representing time, unit is the second, and the longitudinal axis represents fat percentage.It will be seen that two curves have significant difference in Figure 21, can obtain after analysis, the meansigma methods of hands extracarpal fat information can be higher than the meansigma methods of the fatty information inside wrist.Wherein, the meansigma methods of described fat information is the meansigma methods of the fat percentage that multiple sampled point is corresponding.

Being similar to, inventor also finds that the meansigma methods of the fatty information outside palm is significantly greater than the meansigma methods of the fatty information inside palm, and the meansigma methods of the fatty information outside sole is significantly greater than the meansigma methods of the fatty information inside sole.Therefore, can realize the identification in outside in limbs based on the herein described method of this principle.

In one embodiment, the one second fat information that the second side that described reference information is relative with described first side on described limbs obtains.Such as, body-sensing sensor described in two groups can be set, gather corresponding fat information simultaneously in the first side of described limbs and the second side, and using the fatty information in the second side collection as described reference information.

In present embodiment, by the meansigma methods of relatively more described first fat information and the size of the meansigma methods of described second fat information, described step S140g can identify that whether described first side is the inner side of described limbs.The meansigma methods of described first fat information is the meansigma methods of the fat percentage that multiple sampled points are corresponding in described first fat information, similar, and the meansigma methods of described second fat information is the meansigma methods of the fat percentage that multiple sampled points are corresponding in described second fat information.By using meansigma methods, single sampled point can be avoided to cause identifying mistake in the case of sampling error occurs, improve recognition accuracy.Concrete, seeing Figure 22, described step S140g may include that

S141g: in response to described first fat information meansigma methods less than described second fat information meansigma methods, identify that described first side is the inner side of described limbs；

S142g: in response to described first fat information meansigma methods more than described second fat information meansigma methods, identify that described first side is not the inner side of described limbs.

In another embodiment, the threshold value that described reference information can be the inner side fat information according to described limbs and outside fat information determines.Concrete, seeing Figure 23, described step S140g may include that

S141g ': the meansigma methods in response to described first fat information is less than described threshold value, identifies that described first side is the inner side of described limbs；

S142g ': the meansigma methods in response to described first fat information is more than described threshold value, identifies that described first side is not the inner side of described limbs.

Such as, gather the inner side fat information of described limbs and the outside fat information of described limbs in advance, and analyze and process, it is assumed that the meansigma methods of described inner side fat information falls into the first interval (I_min,I_max), it is assumed that the meansigma methods of described outside fat information falls into the second interval (O_min,O_max), then have I_max＜ O_min, then may determine that described threshold value is M, and I_max＜ M ＜ O_min.It is to say, described threshold value M is a numerical value between described first interval and described second interval.

Therefore, if the meansigma methods of described first fat information is less than described threshold value M, then it is assumed that it falls into described first interval, and described first side is the inner side of described limbs；If the meansigma methods of described first fat information is more than described threshold value M, then it is assumed that it falls into described second interval, and described first side is not the inner side of described limbs, is i.e. the outside of described limbs.

Seeing Figure 24, in one embodiment, described method can also include:

S150: perform operation according to recognition result.

Such as, show that described first side is the inner side of described limbs according to recognition result, then can continue to gather in described first side the body-sensing signal of described user；If showing that described first side is not the inner side of described limbs, then can stop at described first side and gather the body-sensing signal of described user, and gather the body-sensing signal of described user in the second side relative with described first side.Described body-sensing signal includes body skin conductance information, body temperature information, acid-base value information, PPG information, humidity information, blood oxygenation information, fat information etc..

Assume that the inner side and outer side of the intelligent watch correspondence limbs that user wears is respectively provided with body-sensing sensor described in a group, so user is when wearing wrist-watch, without considering wearing mode, described intelligent watch can be automatically stopped the body-sensing working sensor outside contact limbs, and ensure to contact the working sensor inside limbs, thus improve Consumer's Experience.

Additionally, the embodiment of the present application also provides for a kind of computer-readable medium, the computer-readable instruction including carrying out following operation when executed: perform step S120 and the operation of S140 of method in above-mentioned Fig. 1 illustrated embodiment.

To sum up, whether method described in the embodiment of the present application, can be the inner side of described limbs according to the first side described in the first body-sensing information of the first side of user one limbs and a reference information identification, it is possible to perform corresponding operating according to recognition result, improve Consumer's Experience.

Figure 25 is the modular structure schematic diagram that the interior outside of limbs described in one embodiment of the invention identifies equipment, in described limbs, outside identifies that equipment can be arranged in the Wearable device such as Intelligent spire lamella, intelligent watch as a functional module, the most also can be as an independent Wearable device for user.As shown in figure 25, described equipment 2500 may include that

One first acquisition module 2510, for obtaining one first body-sensing information of the first side of limbs of user, described first side is inner side or the outside of described limbs；

One identification module 2520, for according to described first body-sensing information and a reference information, identifies that whether described first side is the inner side of described limbs.

Equipment described in the embodiment of the present application, obtain the first body-sensing information of the first side of limbs of user, and then be whether the inner side of described limbs according to the first side described in described first body-sensing information and a reference information identification, thus outside identifies equipment in providing a kind of limbs, the Wearable device being conducive to user is arranged automatically according to recognition result, promotes Consumer's Experience.

Below with reference to detailed description of the invention, describe described first acquisition module 2510 and the function of identification module 2520 in detail.

Described first acquisition module 2510, for obtaining one first body-sensing information of the first side of limbs of user, described first side is inner side or the outside of described limbs.

Described identification module 2520, for according to described first body-sensing information and a reference information, identifies that whether described first side is the inner side of described limbs.

A) described first body-sensing information can be the skin conductance information of described first side, the i.e. first skin conductance information.According to described first skin conductance information and a reference information, described identification module 2520 can identify that whether described first side is the inner side of described limbs.

In one embodiment, the Second Skin conduction information that the second side that described reference information is relative with described first side on described limbs obtains.Seeing Figure 26, described equipment 2500 can also include:

One second acquisition module 2530a, the Second Skin conduction information that obtains for the second side relative with described first side on described limbs is as described reference information.

In present embodiment, described identification module 2520 can be by the meansigma methods of relatively described first skin conductance information and the size of the meansigma methods of described Second Skin conduction information, identify that whether described first side is the inner side of described limbs, concrete, described identification module 2520 may be used for the meansigma methods more than described Second Skin conduction information of the meansigma methods in response to described first skin conductance information, identifies that described first side is the inner side of described limbs；And, in response to described first skin conductance information meansigma methods less than described Second Skin conduction information meansigma methods, identify that described first side is not the inner side of described limbs.

In another embodiment, described reference information can be the inside skin conduction information according to described limbs and the lateral cutaneous conduction threshold value that determines of information.Concrete, seeing Figure 27, described equipment 2500 may include that

One determines module 2540a, determines that a threshold value is as described reference information for the inside skin conduction information according to described limbs and lateral cutaneous conduction information.

Described identification module 2520 may be used for being more than described threshold value in response to the meansigma methods of described first skin conductance information, identifies that described first side is the inner side of described limbs；And, the meansigma methods in response to described first skin conductance information is less than described threshold value, identifies that described first side is not the inner side of described limbs.

Such as, described determine that module 2540a can gather the inside skin conduction information of described limbs and the lateral cutaneous conduction information of described limbs in advance, and analyze and process, it is assumed that the meansigma methods of described inside skin conduction information falls into the first interval (I_min,I_max), it is assumed that the meansigma methods of described lateral cutaneous conduction information falls into the second interval (O_min,O_max), then have O_max＜ I_min, then may determine that described threshold value is M, and O_max＜ M ＜ I_min.It is to say, described threshold value M is a numerical value between described first interval and described second interval.

Therefore, if the meansigma methods of described first skin conductance information is more than described threshold value M, the most described identification module 2520 thinks that it falls into described first interval, and described first side is the inner side of described limbs；If the meansigma methods of described first skin conductance information is less than described threshold value M, then it is assumed that it falls into described second interval, and described first side is not the inner side of described limbs, is i.e. the outside of described limbs.

B) described first body-sensing information can be the body temperature information of described first side, the i.e. first body temperature information.According to described first body temperature information and a reference information, described identification module 2520 can identify that whether described first side is the inner side of described limbs.

In one embodiment, one second body temperature information that the second side that described reference information is relative with described first side on described limbs obtains.Seeing Figure 28, described equipment 2500 can also include:

One second acquisition module 2530b, obtains one second body temperature information as described reference information for the second side relative with described first side on described limbs.

In present embodiment, by the meansigma methods of relatively described first body temperature information and the size of the meansigma methods of described second body temperature information, described identification module 2520 can identify that whether described first side is the inner side of described limbs.The meansigma methods of described first body temperature information is the meansigma methods of the temperature value that multiple sampled points are corresponding in described first body temperature information, similar, and the meansigma methods of described second body temperature information is the meansigma methods of the temperature value that multiple sampled points are corresponding in described second body temperature information.By using meansigma methods, single sampled point can be avoided to cause identifying mistake in the case of sampling error occurs, improve recognition accuracy.Concrete, in response to the meansigma methods of described first body temperature information more than the meansigma methods of described second body temperature information, described identification module 2520 can identify that described first side is the inner side of described limbs；And, in response to the meansigma methods of described first body temperature information less than the meansigma methods of described second body temperature information, identify that described first side is not the inner side of described limbs.

In another embodiment, the threshold value that described reference information can be the inner side body temperature information according to described limbs and outside body temperature information determines.Concrete, seeing Figure 29, described equipment 2500 may include that

One determines module 2540b, for the threshold value that determines according to inner side body temperature information and the outside body temperature information of described limbs as described reference information.

In response to the meansigma methods of described first body temperature information more than described threshold value, described identification module 2520 can identify that described first side is the inner side of described limbs；And, the meansigma methods in response to described first body temperature information is less than described threshold value, identifies that described first side is not the inner side of described limbs.

Such as, described determine that module 2540b can gather the inner side body temperature information of described limbs and the outside body temperature information of described limbs in advance, and analyze and process, it is assumed that the meansigma methods of described inner side body temperature information falls into the first interval (I_min,I_max), it is assumed that the meansigma methods of described outside body temperature information falls into the second interval (O_min,O_max), then have O_max＜ I_min, then may determine that described threshold value is M, and O_max＜ M ＜ I_min.It is to say, described threshold value M is a numerical value between described first interval and described second interval.

Therefore, if the meansigma methods of described first body temperature information is more than described threshold value M, the most described identification module 2520 thinks that it falls into described first interval, and described first side is the inner side of described limbs；If the meansigma methods of described first body temperature information is less than described threshold value M, then it is assumed that it falls into described second interval, and described first side is not the inner side of described limbs, is i.e. the outside of described limbs.

It should be noted that, if outside identifies that equipment 2500 contacts the inner side and outer side of described limbs in described limbs simultaneously, and there is the conduction of heat by described equipment, the acquisition time of the most described first body temperature information and described second body temperature information should complete within the scheduled time from wearing described equipment, i.e. should be at t described in Fig. 6₁Completed before moment, cause to avoid two strips temperature curve to merge identifying mistake.

C) described first body-sensing information can be the acid-base value information of described first side, the i.e. first acid-base value information.According to described first acid-base value information and a reference information, described identification module 2520 can identify that whether described first side is the inner side of described limbs.

In one embodiment, the one second acid-base value information that the second side that described reference information is relative with described first side on described limbs obtains.Seeing Figure 30, described equipment 2500 can also include:

One second acquisition module 2530c, obtains one second acid-base value information as described reference information for the second side relative with described first side on described limbs.

In present embodiment, by the meansigma methods of relatively described first acid-base value information and the size of the meansigma methods of described second acid-base value information, described identification module 2520 can identify that whether described first side is the inner side of described limbs.The meansigma methods of described first acid-base value information is the meansigma methods of the pH value that multiple sampled points are corresponding in described first acid-base value information, being similar to, the meansigma methods of described second acid-base value information is the meansigma methods of the pH value that multiple sampled points are corresponding in described second acid-base value information.By using meansigma methods, single sampled point can be avoided to cause identifying mistake in the case of sampling error occurs, improve recognition accuracy.Concrete, in response to the meansigma methods of described first acid-base value information less than the meansigma methods of described second acid-base value information, described identification module 2520 can identify that described first side is the inner side of described limbs；And, in response to the meansigma methods of described first acid-base value information more than the meansigma methods of described second acid-base value information, identify that described first side is not the inner side of described limbs.

In another embodiment, the threshold value that described reference information can be the inner side acid-base value information according to described limbs and outside acid-base value information determines.Concrete, seeing Figure 31, described equipment 2500 may include that

One determines module 2540c, for the threshold value that determines according to inner side acid-base value information and the outside acid-base value information of described limbs as described reference information.

In response to the meansigma methods of described first acid-base value information less than described threshold value, described identification module 2520 can identify that described first side is the inner side of described limbs；And, the meansigma methods in response to described first acid-base value information is more than described threshold value, identifies that described first side is not the inner side of described limbs.

Such as, described determine that module 2540c can gather the inner side acid-base value information of described limbs and the outside acid-base value information of described limbs in advance, and analyze and process, it is assumed that the meansigma methods of described inner side acid-base value information falls into the first interval (I_min,I_max), it is assumed that the meansigma methods of described outside acid-base value information falls into the second interval (O_min,O_max), then have I_max＜ O_min, then may determine that described threshold value is M, and I_max＜ M ＜ O_min.It is to say, described threshold value M is a numerical value between described first interval and described second interval.

Therefore, if the meansigma methods of described first acid-base value information is more than described threshold value M, the most described identification module 2520 thinks that it falls into described second interval, and described first side is the outside of described limbs；If the meansigma methods of described first acid-base value information is less than described threshold value M, then it is assumed that it falls into described first interval, and described first side is not the outside of described limbs, is i.e. the inner side of described limbs.

D) described first body-sensing information can be the PPG information of described first side, the i.e. the oneth PPG information.A described PPG information can use reflection mode or transmission mode to obtain.When using reflection mode, the first side that corresponding PPG sensor can be arranged on described limbs obtains；When using transmission mode, the detection signal that the transmitting terminal of corresponding PPG sensor sends receives through the first receiving end, rear flank of described limbs, and described detection signal is without second side relative with described first side.According to a described PPG information and a reference information, described identification module 2520 can identify that whether described first side is the inner side of described limbs.

In one embodiment, one the 2nd PPG information that the second side that described reference information is relative with described first side on described limbs obtains.Seeing Figure 32, described equipment 2500 can also include:

One second acquisition module 2530d, obtains one the 2nd PPG information as described reference information for the second side relative with described first side on described limbs.

In present embodiment, by the averaged amplitude value of a relatively described PPG information and the size of the averaged amplitude value of described 2nd PPG information, described identification module 2520 can identify that whether described first side is the inner side of described limbs.The averaged amplitude value of a described PPG information is the meansigma methods of the PPG range value that multiple sampled points are corresponding in a described PPG information, being similar to, the averaged amplitude value of described 2nd PPG information is the meansigma methods of the PPG range value that multiple sampled points are corresponding in described 2nd PPG information.By using meansigma methods, single sampled point can be avoided to cause identifying mistake in the case of sampling error occurs, improve recognition accuracy.Concrete, in response to the averaged amplitude value of a described PPG information more than the averaged amplitude value of described 2nd PPG information, described identification module 2520 can identify that described first side is the inner side of described limbs；And, in response to the averaged amplitude value of a described PPG information less than the averaged amplitude value of described 2nd PPG information, identify that described first side is not the inner side of described limbs.

In another embodiment, the threshold value that described reference information can be the inner side PPG information according to described limbs and outside P PG information determines.Concrete, seeing Figure 33, equipment 2500 may include that

One determines module 2540d, for the threshold value that determines according to inner side PPG information and the outside P PG information of described limbs as described reference information.

In response to the averaged amplitude value of a described PPG information more than described threshold value, described identification module 2520 can identify that described first side is the inner side of described limbs；And, the averaged amplitude value in response to a described PPG information is less than described threshold value, identifies that described first side is not the inner side of described limbs.

Such as, described inner side PPG information and the outside P PG information of described limbs determining that module 2540d can gather described limbs in advance, and analyze and process, it is assumed that the averaged amplitude value of described inner side PPG information falls into the first interval (I_min,I_max), it is assumed that the averaged amplitude value of described outside P PG information falls into the second interval (O_min,O_max), then have O_max＜ I_min, then may determine that described threshold value is M, and O_max＜ M ＜ I_min.It is to say, described threshold value M is a numerical value between described first interval and described second interval.

Therefore, if the averaged amplitude value of a described PPG information is more than described threshold value M, the most described identification module 2520 thinks that it falls into described first interval, and described first side is the inner side of described limbs；If the averaged amplitude value of a described PPG information is less than described threshold value M, then it is assumed that it falls into described second interval, and described first side is not the inner side of described limbs, is i.e. the outside of described limbs.

E) described first body-sensing information can be the humidity information of described first side, the i.e. first humidity information.According to described first humidity information and a reference information, described identification module 2520 can identify that whether described first side is the inner side of described limbs.

In one embodiment, one second humidity information that the second side that described reference information is relative with described first side on described limbs obtains.Seeing Figure 34, described equipment 2500 can also include:

One second acquisition module 2530e, obtains one second humidity information as described reference information for the second side relative with described first side on described limbs.

In present embodiment, by the meansigma methods of relatively described first humidity information and the size of the meansigma methods of described second humidity information, described identification module 2520 can identify that whether described first side is the inner side of described limbs.The meansigma methods of described first humidity information is the meansigma methods of the humidity value that multiple sampled points are corresponding in described first humidity information, similar, and the meansigma methods of described second humidity information is the meansigma methods of the humidity value that multiple sampled points are corresponding in described second humidity information.By using meansigma methods, single sampled point can be avoided to cause identifying mistake in the case of sampling error occurs, improve recognition accuracy.Concrete, in response to the meansigma methods of described first humidity information more than the meansigma methods of described second humidity information, described identification module 2520 can identify that described first side is the inner side of described limbs；And, in response to the meansigma methods of described first humidity information less than the meansigma methods of described second humidity information, identify that described first side is not the inner side of described limbs.

In another embodiment, the threshold value that described reference information can be the inner side humidity information according to described limbs and outside humidity information determines.Concrete, seeing Figure 35, described equipment 2500 may include that

One determines module 2540e, for the threshold value that determines according to inner side humidity information and the outside humidity information of described limbs as described reference information.

In response to the meansigma methods of described first humidity information more than described threshold value, described identification module 2520 can identify that described first side is the inner side of described limbs；And, the meansigma methods in response to described first humidity information is less than described threshold value, identifies that described first side is not the inner side of described limbs.

Such as, described determine that module 2540b can gather the inner side humidity information of described limbs and the outside humidity information of described limbs in advance, and analyze and process, it is assumed that the meansigma methods of described inner side humidity information falls into the first interval (I_min,I_max), it is assumed that the meansigma methods of described outside humidity information falls into the second interval (O_min,O_max), then have O_max＜ I_min, then may determine that described threshold value is M, and O_max＜ M ＜ I_min.It is to say, described threshold value M is a numerical value between described first interval and described second interval.

Therefore, if the meansigma methods of described first humidity information is more than described threshold value M, the most described identification module 2520 thinks that it falls into described first interval, and described first side is the inner side of described limbs；If the meansigma methods of described first humidity information is less than described threshold value M, then it is assumed that it falls into described second interval, and described first side is not the inner side of described limbs, is i.e. the outside of described limbs.

F) described first body-sensing information can be the blood oxygenation information of described first side, the i.e. first blood oxygenation information.Described blood oxygenation information can be blood oxygen saturation, and it can use reflection mode or transmission mode to obtain.Such as, when using reflection mode to obtain described first blood oxygenation information, the first side that corresponding blood oxygen transducer can be arranged on described limbs obtains；When using transmission mode to obtain described first blood oxygenation information, the detection signal that the transmitting terminal of corresponding blood oxygen transducer sends receives through the first receiving end, rear flank of described limbs, and described detection signal is without second side relative with described first side.According to described first blood oxygenation information and a reference information, described identification module 2520 can identify that whether described first side is the inner side of described limbs.

In one embodiment, one second blood oxygenation information that the second side that described reference information is relative with described first side on described limbs obtains.Seeing Figure 36, described equipment 2500 can also include:

One second acquisition module 2530f, obtains one second blood oxygenation information as described reference information for the second side relative with described first side on described limbs.

In present embodiment, by the meansigma methods of relatively described first blood oxygenation information and the size of the meansigma methods of described second blood oxygenation information, described identification module 2520 can identify that whether described first side is the inner side of described limbs.The meansigma methods of described first blood oxygenation information is the meansigma methods of the blood oxygen saturation that multiple sampled points are corresponding in described first blood oxygenation information, being similar to, the meansigma methods of described second blood oxygenation information is the meansigma methods of the blood oxygen saturation that multiple sampled points are corresponding in described second blood oxygenation information.By using meansigma methods, single sampled point can be avoided to cause identifying mistake in the case of sampling error occurs, improve recognition accuracy.Concrete, in response to the meansigma methods of described first blood oxygenation information more than the meansigma methods of described second blood oxygenation information, described identification module 2520 can identify that described first side is the inner side of described limbs；And, in response to the meansigma methods of described first blood oxygenation information less than the meansigma methods of described second blood oxygenation information, identify that described first side is not the inner side of described limbs.

In another embodiment, the threshold value that described reference information can be the inner side blood oxygenation information according to described limbs and outside blood oxygenation information determines.Concrete, seeing Figure 37, described equipment 2500 can also include:

One determines module 2540f, for the threshold value that determines according to inner side blood oxygenation information and the outside blood oxygenation information of described limbs as described reference information.

In response to the meansigma methods of described first blood oxygenation information more than described threshold value, described identification module 2520 can identify that described first side is the inner side of described limbs；And, the meansigma methods in response to described first blood oxygenation information is less than described threshold value, identifies that described first side is not the inner side of described limbs.

Such as, described determine that module 2540f can gather the inner side blood oxygenation information of described limbs and the outside blood oxygenation information of described limbs in advance, and analyze and process, it is assumed that the meansigma methods of described inner side blood oxygenation information falls into the first interval (I_min,I_max), it is assumed that the meansigma methods of described outside blood oxygenation information falls into the second interval (O_min,O_max), then have O_max＜ I_min, then may determine that described threshold value is M, and O_max＜ M ＜ I_min.It is to say, described threshold value M is a numerical value between described first interval and described second interval.

Therefore, if the meansigma methods of described first blood oxygenation information is more than described threshold value M, the most described identification module 2520 thinks that it falls into described first interval, and described first side is the inner side of described limbs；If the meansigma methods of described first blood oxygenation information is less than described threshold value M, then it is assumed that it falls into described second interval, and described first side is not the inner side of described limbs, is i.e. the outside of described limbs.

G) described first body-sensing information can be the fatty information of described first side, the i.e. first fat information.Described fat information can be fat percentage, and such as, described first fat information can be that corresponding fats measurement sensor measures, in the first side of described limbs, the fat percentage obtained.According to a described first fat information and reference information, described identification module 2520 can identify that whether described first side is the inner side of described limbs.

In one embodiment, the one second fat information that the second side that described reference information is relative with described first side on described limbs obtains.Seeing Figure 38, described equipment 2500 can also include:

One second acquisition module 2530g, the one second fat information that obtains for the second side relative with described first side on described limbs is as described reference information.

In present embodiment, by the meansigma methods of relatively more described first fat information and the size of the meansigma methods of described second fat information, described identification module 2520 can identify that whether described first side is the inner side of described limbs.The meansigma methods of described first fat information is the meansigma methods of the fat percentage that multiple sampled points are corresponding in described first fat information, similar, and the meansigma methods of described second fat information is the meansigma methods of the fat percentage that multiple sampled points are corresponding in described second fat information.By using meansigma methods, single sampled point can be avoided to cause identifying mistake in the case of sampling error occurs, improve recognition accuracy.Concrete, in response to the meansigma methods of described first fat information less than the meansigma methods of described second fat information, described identification module can identify that described first side is the inner side of described limbs；And, in response to described first fat information meansigma methods more than described second fat information meansigma methods, identify that described first side is not the inner side of described limbs.

In another embodiment, the threshold value that described reference information can be the inner side fat information according to described limbs and outside fat information determines.Concrete, seeing Figure 39, described equipment 2500 may include that

One determines module 2540g, for the threshold value that determines according to inner side fat information and the outside fat information of described limbs as described reference information.

In response to the meansigma methods of described first fat information less than described threshold value, described identification module 2520 can identify that described first side is the inner side of described limbs；And, the meansigma methods in response to described first fat information is more than described threshold value, identifies that described first side is not the inner side of described limbs.

Such as, described determine that module 2540g can gather the inner side fat information of described limbs and the outside fat information of described limbs in advance, and analyze and process, it is assumed that the meansigma methods of described inner side fat information falls into the first interval (I_min,I_max), it is assumed that the meansigma methods of described outside fat information falls into the second interval (O_min,O_max), then have I_max＜ O_min, then may determine that described threshold value is M, and I_max＜ M ＜ O_min.It is to say, described threshold value M is a numerical value between described first interval and described second interval.

Therefore, if the meansigma methods of described first fat information is less than described threshold value M, the most described identification module 2520 thinks that it falls into described first interval, and described first side is the inner side of described limbs；If the meansigma methods of described first fat information is more than described threshold value M, then it is assumed that it falls into described second interval, and described first side is not the inner side of described limbs, is i.e. the outside of described limbs.

Seeing Figure 40, in one embodiment, described equipment 2500 can also include:

One performs module 2550, for performing operation according to recognition result.

Such as, showing that described first side is the inner side of described limbs according to recognition result, the most described execution module 2550 can control described equipment 2500 and continue to gather in described first side the body-sensing signal of described user；If showing that described first side is not the inner side of described limbs, then can control described equipment 2500 and stop at the body-sensing signal of the described first described user of side collection, and gather the body-sensing signal of described user in the second side relative with described first side.

In limbs described in another embodiment of the application, outside identifies the hardware configuration of equipment as shown in figure 41.To outside in described limbs, the application specific embodiment does not identify that equipment implements and limits, seeing Figure 41, described equipment 4100 may include that

Processor (processor) 4110, communication interface (Communications Interface) 4120, memorizer (memory) 4130, and communication bus 4140.Wherein:

Processor 4110, communication interface 4120, and memorizer 4130 completes mutual communication by communication bus 4140.

Communication interface 4120, is used for and other net element communications.

Processor 4110, is used for the program that performs 4132, specifically can perform the correlation step in the embodiment of the method shown in above-mentioned Fig. 1.

Specifically, program 4132 can include that program code, described program code include computer-managed instruction.

Processor 4110 is probably a central processor CPU, or specific integrated circuit ASIC (Application Specific Integrated Circuit), or is configured to implement one or more integrated circuits of the embodiment of the present application.

Memorizer 4130, is used for program of depositing 4132.Memorizer 4130 may comprise high-speed RAM memorizer, it is also possible to also includes nonvolatile memory (non-volatile memory), for example, at least one disk memory.Program 4132 specifically can perform following steps:

In program 4132 each step implement the corresponding steps or module that may refer in above-described embodiment, be not repeated herein.Those skilled in the art is it can be understood that arrive, and for convenience and simplicity of description, the equipment of foregoing description and the specific works process of module, the corresponding process being referred in preceding method embodiment describes, do not repeats them here.

Those of ordinary skill in the art are it is to be appreciated that combine the unit of each example and the method step that the embodiments described herein describes, it is possible to being implemented in combination in of electronic hardware or computer software and electronic hardware.These functions perform with hardware or software mode actually, depend on application-specific and the design constraint of technical scheme.Professional and technical personnel specifically should can be used for using different methods to realize described function to each, but this realization is it is not considered that exceed scope of the present application.

If described function is using the form realization of SFU software functional unit and as independent production marketing or use, can be stored in a computer read/write memory medium.Based on such understanding, part or the part of this technical scheme that prior art is contributed by the technical scheme of the application the most in other words can embody with the form of software product, this computer software product is stored in a storage medium, including some instructions with so that a computer equipment (can be personal computer, controller, or the network equipment etc.) perform all or part of step of method described in each embodiment of the application.And aforesaid storage medium includes: USB flash disk, portable hard drive, read only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), the various media that can store program code such as magnetic disc or CD.

Embodiment of above is merely to illustrate the application; and not restriction to the application; those of ordinary skill about technical field; in the case of without departing from spirit and scope; can also make a variety of changes and modification; the technical scheme of the most all equivalents falls within the category of the application, and the scope of patent protection of the application should be defined by the claims.

Claims

1. outside recognition methods in limbs, it is characterised in that described method includes:

Obtaining one first humidity information of the first side of limbs of user, described first side is described limbs Inner side or outside；

According to described first humidity information and a reference information, identify whether described first side is described limbs Inner side.

2. the method for claim 1, it is characterised in that described reference information is on described limbs One second humidity information that second side relative with described first side obtains.

3. method as claimed in claim 2, it is characterised in that described according to described first humidity information and One reference information, identifies that whether described first side is that the inner side of described limbs includes:

Big by the meansigma methods of the meansigma methods of relatively described first humidity information and described second humidity information Little, identify that whether described first side is the inner side of described limbs.

4. method as claimed in claim 3, it is characterised in that described by the most described first humidity letter The meansigma methods of breath and the size of the meansigma methods of described second humidity information, identify whether described first side is described The inner side of limbs includes:

Meansigma methods in response to described first humidity information is more than the meansigma methods of described second humidity information, identifies Described first side is the inner side of described limbs；

Meansigma methods in response to described first humidity information is less than the meansigma methods of described second humidity information, identifies Described first side is not the inner side of described limbs.

5. the method for claim 1, it is characterised in that described reference information is according to described limbs Inner side humidity information and the threshold value that determines of outside humidity information.

6. method as claimed in claim 5, it is characterised in that described according to described first humidity information and One reference information, identifies that whether described first side is that the inner side of described limbs includes:

Meansigma methods in response to described first humidity information is more than described threshold value, identifies that described first side is described The inner side of limbs；

Meansigma methods in response to described first humidity information is less than described threshold value, identifies that described first side is not institute State the inner side of limbs.

7. the method as described in any one of claim 1 to 6, it is characterised in that described method also includes:

Operation is performed according to recognition result.

8. method as claimed in claim 7, it is characterised in that described according to recognition result execution operation bag Include:

It is the inner side of described limbs in response to described first side, continues to gather described user's in described first side Body-sensing signal, described body-sensing signal includes body skin conductance information, body temperature information, acid-base value information, PPG Information, humidity information, blood oxygenation information, fat information.

9. in limbs, outside identifies equipment, it is characterised in that described equipment includes:

One first acquisition module, for obtaining one first humidity information of the first side of limbs of user, institute State inner side or outside that the first side is described limbs；

One identification module, for according to described first humidity information and a reference information, identifies described first side It it is whether the inner side of described limbs.

10. equipment as claimed in claim 9, it is characterised in that described equipment also includes:

One second acquisition module, obtains one for the second side relative with described first side on described limbs Two humidity information are as described reference information.

11. equipment as claimed in claim 10, it is characterised in that described identification module, for by than The meansigma methods of more described first humidity information and the size of the meansigma methods of described second humidity information, identify described Whether the first side is the inner side of described limbs.

12. equipment as claimed in claim 11, it is characterised in that described identification module, in response to The meansigma methods of described first humidity information, more than the meansigma methods of described second humidity information, identifies described first side It it is the inner side of described limbs；And

13. equipment as claimed in claim 9, it is characterised in that described equipment also includes:

One determines module, for determining a threshold according to inner side humidity information and the outside humidity information of described limbs Value is as described reference information.

14. equipment as claimed in claim 13, it is characterised in that described identification module, in response to The meansigma methods of described first humidity information is more than described threshold value, identifies that described first side is the inner side of described limbs； And

15. equipment as described in any one of claim 9 to 14, it is characterised in that described equipment also includes:

One performs module, for performing operation according to recognition result.

16. equipment as claimed in claim 15, it is characterised in that described execution module, are used for responding It is the inner side of described limbs in described first side, continues to gather in described first side the body-sensing signal of described user, Described body-sensing signal includes body skin conductance information, body temperature information, acid-base value information, PPG information, humidity Information, blood oxygenation information, fat information.

17. equipment as described in any one of claim 9, it is characterised in that described equipment is one wearable Equipment.

Outside recognition methods in 18. 1 kinds of limbs, it is characterised in that described method includes:

Obtaining one first body-sensing information of the first side of limbs of user, described first side is described limbs Inner side or outside；

According to described first body-sensing information and a reference information, identify whether described first side is described limbs Inner side.

In 19. 1 kinds of limbs, outside identifies equipment, it is characterised in that described equipment includes:

One first acquisition module, for obtaining one first body-sensing information of the first side of limbs of user, institute State inner side or outside that the first side is described limbs；

One identification module, for according to described first body-sensing information and a reference information, identifies described first side It it is whether the inner side of described limbs.